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Posted to commits@commons.apache.org by tn...@apache.org on 2012/02/12 19:07:54 UTC
svn commit: r1243286 - in /commons/proper/math/trunk/src:
main/java/org/apache/commons/math/stat/inference/
test/java/org/apache/commons/math/ test/java/org/apache/commons/math/random/
test/java/org/apache/commons/math/stat/inference/
Author: tn
Date: Sun Feb 12 18:07:53 2012
New Revision: 1243286
URL: http://svn.apache.org/viewvc?rev=1243286&view=rev
Log:
Merged ChiSquareTest implementation and interface, removed use of MathException.
JIRA: MATH-488, MATH-739
Removed:
commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/inference/ChiSquareTestImpl.java
commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/inference/UnknownDistributionChiSquareTest.java
Modified:
commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/inference/ChiSquareTest.java
commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/inference/TestUtils.java
commons/proper/math/trunk/src/test/java/org/apache/commons/math/TestUtils.java
commons/proper/math/trunk/src/test/java/org/apache/commons/math/random/RandomDataTest.java
commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/inference/ChiSquareTestTest.java
commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/inference/TestUtilsTest.java
Modified: commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/inference/ChiSquareTest.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/inference/ChiSquareTest.java?rev=1243286&r1=1243285&r2=1243286&view=diff
==============================================================================
--- commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/inference/ChiSquareTest.java (original)
+++ commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/inference/ChiSquareTest.java Sun Feb 12 18:07:53 2012
@@ -16,43 +16,104 @@
*/
package org.apache.commons.math.stat.inference;
-import org.apache.commons.math.MathException;
+import org.apache.commons.math.distribution.ChiSquaredDistribution;
+import org.apache.commons.math.exception.DimensionMismatchException;
+import org.apache.commons.math.exception.MaxCountExceededException;
+import org.apache.commons.math.exception.NotPositiveException;
+import org.apache.commons.math.exception.NotStrictlyPositiveException;
+import org.apache.commons.math.exception.NullArgumentException;
+import org.apache.commons.math.exception.OutOfRangeException;
+import org.apache.commons.math.exception.ZeroException;
+import org.apache.commons.math.exception.util.LocalizedFormats;
+import org.apache.commons.math.util.FastMath;
+import org.apache.commons.math.util.MathUtils;
/**
- * An interface for Chi-Square tests.
- * <p>This interface handles only known distributions. If the distribution is
- * unknown and should be provided by a sample, then the {@link UnknownDistributionChiSquareTest
- * UnknownDistributionChiSquareTest} extended interface should be used instead.</p>
+ * Implements Chi-Square test statistics.
+ * <p>This implementation handles both, known and unknown distributions.</p>
+ * <p>Two samples tests are used when the distribution is unknown <i>a priori</i>
+ * but provided by one sample. We compare the second sample against the first.</p>
+ *
* @version $Id$
*/
-public interface ChiSquareTest {
+public class ChiSquareTest {
- /**
+ /**
+ * Construct a ChiSquareTest
+ */
+ public ChiSquareTest() {
+ super();
+ }
+
+ /**
* Computes the <a href="http://www.itl.nist.gov/div898/handbook/eda/section3/eda35f.htm">
* Chi-Square statistic</a> comparing <code>observed</code> and <code>expected</code>
* frequency counts.
* <p>
- * This statistic can be used to perform a Chi-Square test evaluating the null hypothesis that
- * the observed counts follow the expected distribution.</p>
+ * This statistic can be used to perform a Chi-Square test evaluating the null
+ * hypothesis that the observed counts follow the expected distribution.</p>
* <p>
* <strong>Preconditions</strong>: <ul>
* <li>Expected counts must all be positive.
* </li>
- * <li>Observed counts must all be >= 0.
+ * <li>Observed counts must all be ≥ 0.
* </li>
* <li>The observed and expected arrays must have the same length and
* their common length must be at least 2.
* </li></ul></p><p>
* If any of the preconditions are not met, an
* <code>IllegalArgumentException</code> is thrown.</p>
+ * <p><strong>Note: </strong>This implementation rescales the
+ * <code>expected</code> array if necessary to ensure that the sum of the
+ * expected and observed counts are equal.</p>
*
* @param observed array of observed frequency counts
* @param expected array of expected frequency counts
- * @return chiSquare statistic
- * @throws IllegalArgumentException if preconditions are not met
+ * @return chiSquare test statistic
+ * @throws NotPositiveException if one element of <code>expected</code> is not
+ * positive
+ * @throws NotStrictlyPositiveException if one element of <code>observed</code> is
+ * not strictly positive
+ * @throws DimensionMismatchException if the arrays length is less than 2
*/
- double chiSquare(double[] expected, long[] observed)
- throws IllegalArgumentException;
+ public double chiSquare(final double[] expected, final long[] observed)
+ throws NotPositiveException, NotStrictlyPositiveException,
+ DimensionMismatchException {
+
+ if (expected.length < 2) {
+ throw new DimensionMismatchException(expected.length, 2);
+ }
+ if (expected.length != observed.length) {
+ throw new DimensionMismatchException(expected.length, observed.length);
+ }
+ checkPositive(expected);
+ checkNonNegative(observed);
+
+ double sumExpected = 0d;
+ double sumObserved = 0d;
+ for (int i = 0; i < observed.length; i++) {
+ sumExpected += expected[i];
+ sumObserved += observed[i];
+ }
+ double ratio = 1.0d;
+ boolean rescale = false;
+ if (FastMath.abs(sumExpected - sumObserved) > 10E-6) {
+ ratio = sumObserved / sumExpected;
+ rescale = true;
+ }
+ double sumSq = 0.0d;
+ for (int i = 0; i < observed.length; i++) {
+ if (rescale) {
+ final double dev = observed[i] - ratio * expected[i];
+ sumSq += dev * dev / (ratio * expected[i]);
+ } else {
+ final double dev = observed[i] - expected[i];
+ sumSq += dev * dev / expected[i];
+ }
+ }
+ return sumSq;
+
+ }
/**
* Returns the <i>observed significance level</i>, or <a href=
@@ -69,29 +130,43 @@ public interface ChiSquareTest {
* <strong>Preconditions</strong>: <ul>
* <li>Expected counts must all be positive.
* </li>
- * <li>Observed counts must all be >= 0.
+ * <li>Observed counts must all be ≥ 0.
* </li>
* <li>The observed and expected arrays must have the same length and
* their common length must be at least 2.
* </li></ul></p><p>
* If any of the preconditions are not met, an
* <code>IllegalArgumentException</code> is thrown.</p>
+ * <p><strong>Note: </strong>This implementation rescales the
+ * <code>expected</code> array if necessary to ensure that the sum of the
+ * expected and observed counts are equal.</p>
*
* @param observed array of observed frequency counts
* @param expected array of expected frequency counts
* @return p-value
- * @throws IllegalArgumentException if preconditions are not met
- * @throws MathException if an error occurs computing the p-value
+ * @throws NotPositiveException if one element of <code>expected</code> is not
+ * positive
+ * @throws NotStrictlyPositiveException if one element of <code>observed</code> is
+ * not strictly positive
+ * @throws DimensionMismatchException if the arrays length is less than 2
+ * @throws MaxCountExceededException if an error occurs computing the p-value
*/
- double chiSquareTest(double[] expected, long[] observed)
- throws IllegalArgumentException, MathException;
+ public double chiSquareTest(final double[] expected, final long[] observed)
+ throws NotPositiveException, NotStrictlyPositiveException,
+ DimensionMismatchException, MaxCountExceededException {
+
+ ChiSquaredDistribution distribution =
+ new ChiSquaredDistribution(expected.length - 1.0);
+ return 1.0 - distribution.cumulativeProbability(chiSquare(expected, observed));
+
+ }
/**
* Performs a <a href="http://www.itl.nist.gov/div898/handbook/eda/section3/eda35f.htm">
- * Chi-square goodness of fit test</a> evaluating the null hypothesis that the observed counts
- * conform to the frequency distribution described by the expected counts, with
- * significance level <code>alpha</code>. Returns true iff the null hypothesis can be rejected
- * with 100 * (1 - alpha) percent confidence.
+ * Chi-square goodness of fit test</a> evaluating the null hypothesis that the
+ * observed counts conform to the frequency distribution described by the expected
+ * counts, with significance level <code>alpha</code>. Returns true iff the null
+ * hypothesis can be rejected with 100 * (1 - alpha) percent confidence.
* <p>
* <strong>Example:</strong><br>
* To test the hypothesis that <code>observed</code> follows
@@ -101,25 +176,43 @@ public interface ChiSquareTest {
* <strong>Preconditions</strong>: <ul>
* <li>Expected counts must all be positive.
* </li>
- * <li>Observed counts must all be >= 0.
+ * <li>Observed counts must all be ≥ 0.
* </li>
* <li>The observed and expected arrays must have the same length and
* their common length must be at least 2.
- * <li> <code> 0 < alpha < 0.5 </code>
+ * <li> <code> 0 < alpha < 0.5 </code>
* </li></ul></p><p>
* If any of the preconditions are not met, an
* <code>IllegalArgumentException</code> is thrown.</p>
+ * <p><strong>Note: </strong>This implementation rescales the
+ * <code>expected</code> array if necessary to ensure that the sum of the
+ * expected and observed counts are equal.</p>
*
* @param observed array of observed frequency counts
* @param expected array of expected frequency counts
* @param alpha significance level of the test
* @return true iff null hypothesis can be rejected with confidence
* 1 - alpha
- * @throws IllegalArgumentException if preconditions are not met
- * @throws MathException if an error occurs performing the test
+ * @throws NotPositiveException if one element of <code>expected</code> is not
+ * positive
+ * @throws NotStrictlyPositiveException if one element of <code>observed</code> is
+ * not strictly positive
+ * @throws DimensionMismatchException if the arrays length is less than 2
+ * @throws OutOfRangeException if <code>alpha</code> is not in the range (0, 0.5]
+ * @throws MaxCountExceededException if an error occurs computing the p-value
*/
- boolean chiSquareTest(double[] expected, long[] observed, double alpha)
- throws IllegalArgumentException, MathException;
+ public boolean chiSquareTest(final double[] expected, final long[] observed,
+ final double alpha)
+ throws NotPositiveException, NotStrictlyPositiveException,
+ DimensionMismatchException, OutOfRangeException, MaxCountExceededException {
+
+ if ((alpha <= 0) || (alpha > 0.5)) {
+ throw new OutOfRangeException(LocalizedFormats.OUT_OF_BOUND_SIGNIFICANCE_LEVEL,
+ alpha, 0, 0.5);
+ }
+ return chiSquareTest(expected, observed) < alpha;
+
+ }
/**
* Computes the Chi-Square statistic associated with a
@@ -131,7 +224,7 @@ public interface ChiSquareTest {
* <code>count[0], ... , count[count.length - 1] </code></p>
* <p>
* <strong>Preconditions</strong>: <ul>
- * <li>All counts must be >= 0.
+ * <li>All counts must be ≥ 0.
* </li>
* <li>The count array must be rectangular (i.e. all count[i] subarrays
* must have the same length).
@@ -144,11 +237,44 @@ public interface ChiSquareTest {
* <code>IllegalArgumentException</code> is thrown.</p>
*
* @param counts array representation of 2-way table
- * @return chiSquare statistic
- * @throws IllegalArgumentException if preconditions are not met
+ * @return chiSquare test statistic
+ * @throws NullArgumentException if the array is null
+ * @throws DimensionMismatchException if the array is not rectangular
+ * @throws NotPositiveException if one entry is not positive
*/
- double chiSquare(long[][] counts)
- throws IllegalArgumentException;
+ public double chiSquare(final long[][] counts)
+ throws NullArgumentException, NotPositiveException,
+ DimensionMismatchException {
+
+ checkArray(counts);
+ int nRows = counts.length;
+ int nCols = counts[0].length;
+
+ // compute row, column and total sums
+ double[] rowSum = new double[nRows];
+ double[] colSum = new double[nCols];
+ double total = 0.0d;
+ for (int row = 0; row < nRows; row++) {
+ for (int col = 0; col < nCols; col++) {
+ rowSum[row] += counts[row][col];
+ colSum[col] += counts[row][col];
+ total += counts[row][col];
+ }
+ }
+
+ // compute expected counts and chi-square
+ double sumSq = 0.0d;
+ double expected = 0.0d;
+ for (int row = 0; row < nRows; row++) {
+ for (int col = 0; col < nCols; col++) {
+ expected = (rowSum[row] * colSum[col]) / total;
+ sumSq += ((counts[row][col] - expected) *
+ (counts[row][col] - expected)) / expected;
+ }
+ }
+ return sumSq;
+
+ }
/**
* Returns the <i>observed significance level</i>, or <a href=
@@ -162,12 +288,13 @@ public interface ChiSquareTest {
* <code>count[0], ... , count[count.length - 1] </code></p>
* <p>
* <strong>Preconditions</strong>: <ul>
- * <li>All counts must be >= 0.
+ * <li>All counts must be ≥ 0.
* </li>
- * <li>The count array must be rectangular (i.e. all count[i] subarrays must have the same length).
+ * <li>The count array must be rectangular (i.e. all count[i] subarrays must have
+ * the same length).
* </li>
- * <li>The 2-way table represented by <code>counts</code> must have at least 2 columns and
- * at least 2 rows.
+ * <li>The 2-way table represented by <code>counts</code> must have at least 2
+ * columns and at least 2 rows.
* </li>
* </li></ul></p><p>
* If any of the preconditions are not met, an
@@ -175,18 +302,30 @@ public interface ChiSquareTest {
*
* @param counts array representation of 2-way table
* @return p-value
- * @throws IllegalArgumentException if preconditions are not met
- * @throws MathException if an error occurs computing the p-value
+ * @throws NullArgumentException if the array is null
+ * @throws DimensionMismatchException if the array is not rectangular
+ * @throws NotPositiveException if one entry is not positive
+ * @throws MaxCountExceededException if an error occurs computing the p-value
*/
- double chiSquareTest(long[][] counts)
- throws IllegalArgumentException, MathException;
+ public double chiSquareTest(final long[][] counts)
+ throws NullArgumentException, DimensionMismatchException,
+ NotPositiveException, MaxCountExceededException {
+
+ checkArray(counts);
+ double df = ((double) counts.length -1) * ((double) counts[0].length - 1);
+ ChiSquaredDistribution distribution;
+ distribution = new ChiSquaredDistribution(df);
+ return 1 - distribution.cumulativeProbability(chiSquare(counts));
+
+ }
/**
* Performs a <a href="http://www.itl.nist.gov/div898/handbook/prc/section4/prc45.htm">
- * chi-square test of independence</a> evaluating the null hypothesis that the classifications
- * represented by the counts in the columns of the input 2-way table are independent of the rows,
- * with significance level <code>alpha</code>. Returns true iff the null hypothesis can be rejected
- * with 100 * (1 - alpha) percent confidence.
+ * chi-square test of independence</a> evaluating the null hypothesis that the
+ * classifications represented by the counts in the columns of the input 2-way table
+ * are independent of the rows, with significance level <code>alpha</code>.
+ * Returns true iff the null hypothesis can be rejected with 100 * (1 - alpha) percent
+ * confidence.
* <p>
* The rows of the 2-way table are
* <code>count[0], ... , count[count.length - 1] </code></p>
@@ -194,17 +333,16 @@ public interface ChiSquareTest {
* <strong>Example:</strong><br>
* To test the null hypothesis that the counts in
* <code>count[0], ... , count[count.length - 1] </code>
- * all correspond to the same underlying probability distribution at the 99% level, use </p><p>
- * <code>chiSquareTest(counts, 0.01) </code></p>
+ * all correspond to the same underlying probability distribution at the 99% level, use</p>
+ * <p><code>chiSquareTest(counts, 0.01)</code></p>
* <p>
* <strong>Preconditions</strong>: <ul>
- * <li>All counts must be >= 0.
- * </li>
- * <li>The count array must be rectangular (i.e. all count[i] subarrays must have the same length).
+ * <li>All counts must be ≥ 0.
* </li>
+ * <li>The count array must be rectangular (i.e. all count[i] subarrays must have the
+ * same length).</li>
* <li>The 2-way table represented by <code>counts</code> must have at least 2 columns and
- * at least 2 rows.
- * </li>
+ * at least 2 rows.</li>
* </li></ul></p><p>
* If any of the preconditions are not met, an
* <code>IllegalArgumentException</code> is thrown.</p>
@@ -213,10 +351,328 @@ public interface ChiSquareTest {
* @param alpha significance level of the test
* @return true iff null hypothesis can be rejected with confidence
* 1 - alpha
- * @throws IllegalArgumentException if preconditions are not met
- * @throws MathException if an error occurs performing the test
+ * @throws NullArgumentException if the array is null
+ * @throws DimensionMismatchException if the array is not rectangular
+ * @throws NotPositiveException if one entry is not positive
+ * @throws OutOfRangeException if <code>alpha</code> is not in the range (0, 0.5]
+ * @throws MaxCountExceededException if an error occurs computing the p-value
+ */
+ public boolean chiSquareTest(final long[][] counts, final double alpha)
+ throws NullArgumentException, DimensionMismatchException,
+ NotPositiveException, OutOfRangeException, MaxCountExceededException {
+
+ if ((alpha <= 0) || (alpha > 0.5)) {
+ throw new OutOfRangeException(LocalizedFormats.OUT_OF_BOUND_SIGNIFICANCE_LEVEL,
+ alpha, 0, 0.5);
+ }
+ return chiSquareTest(counts) < alpha;
+
+ }
+
+ /**
+ * <p>Computes a
+ * <a href="http://www.itl.nist.gov/div898/software/dataplot/refman1/auxillar/chi2samp.htm">
+ * Chi-Square two sample test statistic</a> comparing bin frequency counts
+ * in <code>observed1</code> and <code>observed2</code>. The
+ * sums of frequency counts in the two samples are not required to be the
+ * same. The formula used to compute the test statistic is</p>
+ * <code>
+ * ∑[(K * observed1[i] - observed2[i]/K)<sup>2</sup> / (observed1[i] + observed2[i])]
+ * </code> where
+ * <br/><code>K = &sqrt;[&sum(observed2 / ∑(observed1)]</code>
+ * </p>
+ * <p>This statistic can be used to perform a Chi-Square test evaluating the
+ * null hypothesis that both observed counts follow the same distribution.</p>
+ * <p>
+ * <strong>Preconditions</strong>: <ul>
+ * <li>Observed counts must be non-negative.
+ * </li>
+ * <li>Observed counts for a specific bin must not both be zero.
+ * </li>
+ * <li>Observed counts for a specific sample must not all be 0.
+ * </li>
+ * <li>The arrays <code>observed1</code> and <code>observed2</code> must have
+ * the same length and their common length must be at least 2.
+ * </li></ul></p><p>
+ * If any of the preconditions are not met, an
+ * <code>IllegalArgumentException</code> is thrown.</p>
+ *
+ * @param observed1 array of observed frequency counts of the first data set
+ * @param observed2 array of observed frequency counts of the second data set
+ * @return chiSquare test statistic
+ * @throws DimensionMismatchException the the length of the arrays does not match
+ * @throws NotPositiveException if one entry in <code>observed1</code> or
+ * <code>observed2</code> is not positive
+ * @throws ZeroException if either all counts of <code>observed1</code> or
+ * <code>observed2</code> are zero, or if the count at the same index is zero
+ * for both arrays
+ * @since 1.2
+ */
+ public double chiSquareDataSetsComparison(long[] observed1, long[] observed2)
+ throws DimensionMismatchException, NotPositiveException, ZeroException {
+
+ // Make sure lengths are same
+ if (observed1.length < 2) {
+ throw new DimensionMismatchException(observed1.length, 2);
+ }
+ if (observed1.length != observed2.length) {
+ throw new DimensionMismatchException(observed1.length, observed2.length);
+ }
+
+ // Ensure non-negative counts
+ checkNonNegative(observed1);
+ checkNonNegative(observed2);
+
+ // Compute and compare count sums
+ long countSum1 = 0;
+ long countSum2 = 0;
+ boolean unequalCounts = false;
+ double weight = 0.0;
+ for (int i = 0; i < observed1.length; i++) {
+ countSum1 += observed1[i];
+ countSum2 += observed2[i];
+ }
+ // Ensure neither sample is uniformly 0
+ if (countSum1 == 0 || countSum2 == 0) {
+ throw new ZeroException();
+ }
+ // Compare and compute weight only if different
+ unequalCounts = countSum1 != countSum2;
+ if (unequalCounts) {
+ weight = FastMath.sqrt((double) countSum1 / (double) countSum2);
+ }
+ // Compute ChiSquare statistic
+ double sumSq = 0.0d;
+ double dev = 0.0d;
+ double obs1 = 0.0d;
+ double obs2 = 0.0d;
+ for (int i = 0; i < observed1.length; i++) {
+ if (observed1[i] == 0 && observed2[i] == 0) {
+ throw new ZeroException(LocalizedFormats.OBSERVED_COUNTS_BOTTH_ZERO_FOR_ENTRY, i);
+ } else {
+ obs1 = observed1[i];
+ obs2 = observed2[i];
+ if (unequalCounts) { // apply weights
+ dev = obs1/weight - obs2 * weight;
+ } else {
+ dev = obs1 - obs2;
+ }
+ sumSq += (dev * dev) / (obs1 + obs2);
+ }
+ }
+ return sumSq;
+ }
+
+ /**
+ * <p>Returns the <i>observed significance level</i>, or <a href=
+ * "http://www.cas.lancs.ac.uk/glossary_v1.1/hyptest.html#pvalue">
+ * p-value</a>, associated with a Chi-Square two sample test comparing
+ * bin frequency counts in <code>observed1</code> and
+ * <code>observed2</code>.
+ * </p>
+ * <p>The number returned is the smallest significance level at which one
+ * can reject the null hypothesis that the observed counts conform to the
+ * same distribution.
+ * </p>
+ * <p>See {@link #chiSquareDataSetsComparison(long[], long[])} for details
+ * on the formula used to compute the test statistic. The degrees of
+ * of freedom used to perform the test is one less than the common length
+ * of the input observed count arrays.
+ * </p>
+ * <strong>Preconditions</strong>: <ul>
+ * <li>Observed counts must be non-negative.
+ * </li>
+ * <li>Observed counts for a specific bin must not both be zero.
+ * </li>
+ * <li>Observed counts for a specific sample must not all be 0.
+ * </li>
+ * <li>The arrays <code>observed1</code> and <code>observed2</code> must
+ * have the same length and
+ * their common length must be at least 2.
+ * </li></ul><p>
+ * If any of the preconditions are not met, an
+ * <code>IllegalArgumentException</code> is thrown.</p>
+ *
+ * @param observed1 array of observed frequency counts of the first data set
+ * @param observed2 array of observed frequency counts of the second data set
+ * @return p-value
+ * @throws DimensionMismatchException the the length of the arrays does not match
+ * @throws NotPositiveException if one entry in <code>observed1</code> or
+ * <code>observed2</code> is not positive
+ * @throws ZeroException if either all counts of <code>observed1</code> or
+ * <code>observed2</code> are zero, or if the count at the same index is zero
+ * for both arrays
+ * @throws MaxCountExceededException if an error occurs computing the p-value
+ * @since 1.2
*/
- boolean chiSquareTest(long[][] counts, double alpha)
- throws IllegalArgumentException, MathException;
+ public double chiSquareTestDataSetsComparison(long[] observed1, long[] observed2)
+ throws DimensionMismatchException, NotPositiveException, ZeroException,
+ MaxCountExceededException {
+
+ ChiSquaredDistribution distribution;
+ distribution = new ChiSquaredDistribution((double) observed1.length - 1);
+ return 1 - distribution.cumulativeProbability(
+ chiSquareDataSetsComparison(observed1, observed2));
+
+ }
+
+ /**
+ * <p>Performs a Chi-Square two sample test comparing two binned data
+ * sets. The test evaluates the null hypothesis that the two lists of
+ * observed counts conform to the same frequency distribution, with
+ * significance level <code>alpha</code>. Returns true iff the null
+ * hypothesis can be rejected with 100 * (1 - alpha) percent confidence.
+ * </p>
+ * <p>See {@link #chiSquareDataSetsComparison(long[], long[])} for
+ * details on the formula used to compute the Chisquare statistic used
+ * in the test. The degrees of of freedom used to perform the test is
+ * one less than the common length of the input observed count arrays.
+ * </p>
+ * <strong>Preconditions</strong>: <ul>
+ * <li>Observed counts must be non-negative.
+ * </li>
+ * <li>Observed counts for a specific bin must not both be zero.
+ * </li>
+ * <li>Observed counts for a specific sample must not all be 0.
+ * </li>
+ * <li>The arrays <code>observed1</code> and <code>observed2</code> must
+ * have the same length and their common length must be at least 2.
+ * </li>
+ * <li> <code> 0 < alpha < 0.5 </code>
+ * </li></ul><p>
+ * If any of the preconditions are not met, an
+ * <code>IllegalArgumentException</code> is thrown.</p>
+ *
+ * @param observed1 array of observed frequency counts of the first data set
+ * @param observed2 array of observed frequency counts of the second data set
+ * @param alpha significance level of the test
+ * @return true iff null hypothesis can be rejected with confidence
+ * 1 - alpha
+ * @throws DimensionMismatchException the the length of the arrays does not match
+ * @throws NotPositiveException if one entry in <code>observed1</code> or
+ * <code>observed2</code> is not positive
+ * @throws ZeroException if either all counts of <code>observed1</code> or
+ * <code>observed2</code> are zero, or if the count at the same index is zero
+ * for both arrays
+ * @throws OutOfRangeException if <code>alpha</code> is not in the range (0, 0.5]
+ * @throws MaxCountExceededException if an error occurs performing the test
+ * @since 1.2
+ */
+ public boolean chiSquareTestDataSetsComparison(final long[] observed1,
+ final long[] observed2,
+ final double alpha)
+ throws DimensionMismatchException, NotPositiveException,
+ ZeroException, OutOfRangeException, MaxCountExceededException {
+
+ if (alpha <= 0 ||
+ alpha > 0.5) {
+ throw new OutOfRangeException(LocalizedFormats.OUT_OF_BOUND_SIGNIFICANCE_LEVEL,
+ alpha, 0, 0.5);
+ }
+ return chiSquareTestDataSetsComparison(observed1, observed2) < alpha;
+
+ }
+
+ /**
+ * Checks to make sure that the input long[][] array is rectangular,
+ * has at least 2 rows and 2 columns, and has all non-negative entries.
+ *
+ * @param in input 2-way table to check
+ * @throws NullArgumentException if the array is null
+ * @throws DimensionMismatchException if the array is not valid
+ * @throws NotPositiveException if one entry is not positive
+ */
+ private void checkArray(final long[][] in)
+ throws NullArgumentException, DimensionMismatchException,
+ NotPositiveException {
+
+ if (in.length < 2) {
+ throw new DimensionMismatchException(in.length, 2);
+ }
+
+ if (in[0].length < 2) {
+ throw new DimensionMismatchException(in[0].length, 2);
+ }
+
+ checkRectangular(in);
+ checkNonNegative(in);
+
+ }
+
+ //--------------------- Private array methods -- should find a utility home for these
+
+ /**
+ * Throws DimensionMismatchException if the input array is not rectangular.
+ *
+ * @param in array to be tested
+ * @throws NullArgumentException if input array is null
+ * @throws DimensionMismatchException if input array is not rectangular
+ */
+ private void checkRectangular(final long[][] in)
+ throws NullArgumentException, DimensionMismatchException {
+
+ MathUtils.checkNotNull(in);
+ for (int i = 1; i < in.length; i++) {
+ if (in[i].length != in[0].length) {
+ throw new DimensionMismatchException(
+ LocalizedFormats.DIFFERENT_ROWS_LENGTHS,
+ in[i].length, in[0].length);
+ }
+ }
+
+ }
+
+ /**
+ * Check all entries of the input array are strictly positive.
+ *
+ * @param in Array to be tested.
+ * @throws NotStrictlyPositiveException if one entry is not strictly positive.
+ */
+ private void checkPositive(final double[] in)
+ throws NotStrictlyPositiveException {
+
+ for (int i = 0; i < in.length; i++) {
+ if (in[i] <= 0) {
+ throw new NotStrictlyPositiveException(in[i]);
+ }
+ }
+
+ }
+
+ /**
+ * Check all entries of the input array are >= 0.
+ *
+ * @param in Array to be tested.
+ * @throws NotPositiveException if one entry is negative.
+ */
+ private void checkNonNegative(final long[] in)
+ throws NotPositiveException {
+
+ for (int i = 0; i < in.length; i++) {
+ if (in[i] < 0) {
+ throw new NotPositiveException(in[i]);
+ }
+ }
+
+ }
+
+ /**
+ * Check all entries of the input array are >= 0.
+ *
+ * @param in Array to be tested.
+ * @throws NotPositiveException if one entry is negative.
+ */
+ private void checkNonNegative(final long[][] in)
+ throws NotPositiveException {
+
+ for (int i = 0; i < in.length; i ++) {
+ for (int j = 0; j < in[i].length; j++) {
+ if (in[i][j] < 0) {
+ throw new NotPositiveException(in[i][j]);
+ }
+ }
+ }
+
+ }
}
Modified: commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/inference/TestUtils.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/inference/TestUtils.java?rev=1243286&r1=1243285&r2=1243286&view=diff
==============================================================================
--- commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/inference/TestUtils.java (original)
+++ commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/inference/TestUtils.java Sun Feb 12 18:07:53 2012
@@ -21,8 +21,11 @@ import org.apache.commons.math.MathExcep
import org.apache.commons.math.exception.ConvergenceException;
import org.apache.commons.math.exception.DimensionMismatchException;
import org.apache.commons.math.exception.MaxCountExceededException;
+import org.apache.commons.math.exception.NotPositiveException;
+import org.apache.commons.math.exception.NotStrictlyPositiveException;
import org.apache.commons.math.exception.NullArgumentException;
import org.apache.commons.math.exception.OutOfRangeException;
+import org.apache.commons.math.exception.ZeroException;
import org.apache.commons.math.stat.descriptive.StatisticalSummary;
/**
@@ -38,22 +41,11 @@ public class TestUtils {
private static final TTest T_TEST = new TTestImpl();
/** Singleton ChiSquareTest instance. */
- private static final ChiSquareTest CHI_SQUARE_TEST = new ChiSquareTestImpl();
-
- /** Singleton ChiSquareTest instance. */
- private static final UnknownDistributionChiSquareTest UNKNOWN_DISTRIBUTION_CHI_SQUARE_TEST =
- new ChiSquareTestImpl();
+ private static final ChiSquareTest CHI_SQUARE_TEST = new ChiSquareTest();
/** Singleton OneWayAnova instance. */
private static final OneWayAnova ONE_WAY_ANANOVA = new OneWayAnova();
- /** Singleton MannWhitneyUTest instance using default ranking. */
- private static final MannWhitneyUTest MANN_WHITNEY_U_TEST = new MannWhitneyUTest();
-
- /** Singleton WilcoxonSignedRankTest instance. */
- private static final WilcoxonSignedRankTest WILCOXON_SIGNED_RANK_TEST =
- new WilcoxonSignedRankTest();
-
/**
* Prevent instantiation.
*/
@@ -234,49 +226,55 @@ public class TestUtils {
/**
* @see org.apache.commons.math.stat.inference.ChiSquareTest#chiSquare(double[], long[])
*/
- public static double chiSquare(double[] expected, long[] observed)
- throws IllegalArgumentException {
+ public static double chiSquare(final double[] expected, final long[] observed)
+ throws NotPositiveException, NotStrictlyPositiveException,
+ DimensionMismatchException {
return CHI_SQUARE_TEST.chiSquare(expected, observed);
}
/**
* @see org.apache.commons.math.stat.inference.ChiSquareTest#chiSquare(long[][])
*/
- public static double chiSquare(long[][] counts)
- throws IllegalArgumentException {
+ public static double chiSquare(final long[][] counts)
+ throws NullArgumentException, NotPositiveException,
+ DimensionMismatchException {
return CHI_SQUARE_TEST.chiSquare(counts);
}
/**
* @see org.apache.commons.math.stat.inference.ChiSquareTest#chiSquareTest(double[], long[], double)
*/
- public static boolean chiSquareTest(double[] expected, long[] observed,
- double alpha)
- throws IllegalArgumentException, MathException {
+ public static boolean chiSquareTest(final double[] expected, final long[] observed,
+ final double alpha)
+ throws NotPositiveException, NotStrictlyPositiveException,
+ DimensionMismatchException, OutOfRangeException, MaxCountExceededException {
return CHI_SQUARE_TEST.chiSquareTest(expected, observed, alpha);
}
/**
* @see org.apache.commons.math.stat.inference.ChiSquareTest#chiSquareTest(double[], long[])
*/
- public static double chiSquareTest(double[] expected, long[] observed)
- throws IllegalArgumentException, MathException {
+ public static double chiSquareTest(final double[] expected, final long[] observed)
+ throws NotPositiveException, NotStrictlyPositiveException,
+ DimensionMismatchException, MaxCountExceededException {
return CHI_SQUARE_TEST.chiSquareTest(expected, observed);
}
/**
* @see org.apache.commons.math.stat.inference.ChiSquareTest#chiSquareTest(long[][], double)
*/
- public static boolean chiSquareTest(long[][] counts, double alpha)
- throws IllegalArgumentException, MathException {
+ public static boolean chiSquareTest(final long[][] counts, final double alpha)
+ throws NullArgumentException, DimensionMismatchException,
+ NotPositiveException, OutOfRangeException, MaxCountExceededException {
return CHI_SQUARE_TEST.chiSquareTest(counts, alpha);
}
/**
* @see org.apache.commons.math.stat.inference.ChiSquareTest#chiSquareTest(long[][])
*/
- public static double chiSquareTest(long[][] counts)
- throws IllegalArgumentException, MathException {
+ public static double chiSquareTest(final long[][] counts)
+ throws NullArgumentException, DimensionMismatchException,
+ NotPositiveException, MaxCountExceededException {
return CHI_SQUARE_TEST.chiSquareTest(counts);
}
@@ -285,9 +283,10 @@ public class TestUtils {
*
* @since 1.2
*/
- public static double chiSquareDataSetsComparison(long[] observed1, long[] observed2)
- throws IllegalArgumentException {
- return UNKNOWN_DISTRIBUTION_CHI_SQUARE_TEST.chiSquareDataSetsComparison(observed1, observed2);
+ public static double chiSquareDataSetsComparison(final long[] observed1,
+ final long[] observed2)
+ throws DimensionMismatchException, NotPositiveException, ZeroException {
+ return CHI_SQUARE_TEST.chiSquareDataSetsComparison(observed1, observed2);
}
/**
@@ -295,21 +294,24 @@ public class TestUtils {
*
* @since 1.2
*/
- public static double chiSquareTestDataSetsComparison(long[] observed1, long[] observed2)
- throws IllegalArgumentException, MathException {
- return UNKNOWN_DISTRIBUTION_CHI_SQUARE_TEST.chiSquareTestDataSetsComparison(observed1, observed2);
+ public static double chiSquareTestDataSetsComparison(final long[] observed1,
+ final long[] observed2)
+ throws DimensionMismatchException, NotPositiveException, ZeroException,
+ MaxCountExceededException {
+ return CHI_SQUARE_TEST.chiSquareTestDataSetsComparison(observed1, observed2);
}
-
/**
* @see org.apache.commons.math.stat.inference.UnknownDistributionChiSquareTest#chiSquareTestDataSetsComparison(long[], long[], double)
*
* @since 1.2
*/
- public static boolean chiSquareTestDataSetsComparison(long[] observed1, long[] observed2,
- double alpha)
- throws IllegalArgumentException, MathException {
- return UNKNOWN_DISTRIBUTION_CHI_SQUARE_TEST.chiSquareTestDataSetsComparison(observed1, observed2, alpha);
+ public static boolean chiSquareTestDataSetsComparison(final long[] observed1,
+ final long[] observed2,
+ final double alpha)
+ throws DimensionMismatchException, NotPositiveException,
+ ZeroException, OutOfRangeException, MaxCountExceededException {
+ return CHI_SQUARE_TEST.chiSquareTestDataSetsComparison(observed1, observed2, alpha);
}
/**
Modified: commons/proper/math/trunk/src/test/java/org/apache/commons/math/TestUtils.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/test/java/org/apache/commons/math/TestUtils.java?rev=1243286&r1=1243285&r2=1243286&view=diff
==============================================================================
--- commons/proper/math/trunk/src/test/java/org/apache/commons/math/TestUtils.java (original)
+++ commons/proper/math/trunk/src/test/java/org/apache/commons/math/TestUtils.java Sun Feb 12 18:07:53 2012
@@ -31,7 +31,6 @@ import org.apache.commons.math.distribut
import org.apache.commons.math.linear.FieldMatrix;
import org.apache.commons.math.linear.RealMatrix;
import org.apache.commons.math.stat.inference.ChiSquareTest;
-import org.apache.commons.math.stat.inference.ChiSquareTestImpl;
import org.apache.commons.math.util.FastMath;
import org.apache.commons.math.util.Precision;
import org.junit.Assert;
@@ -357,7 +356,7 @@ public class TestUtils {
* @param alpha significance level of the test
*/
public static void assertChiSquareAccept(String[] valueLabels, double[] expected, long[] observed, double alpha) throws Exception {
- ChiSquareTest chiSquareTest = new ChiSquareTestImpl();
+ ChiSquareTest chiSquareTest = new ChiSquareTest();
// Fail if we can reject null hypothesis that distributions are the same
if (chiSquareTest.chiSquareTest(expected, observed, alpha)) {
Modified: commons/proper/math/trunk/src/test/java/org/apache/commons/math/random/RandomDataTest.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/test/java/org/apache/commons/math/random/RandomDataTest.java?rev=1243286&r1=1243285&r2=1243286&view=diff
==============================================================================
--- commons/proper/math/trunk/src/test/java/org/apache/commons/math/random/RandomDataTest.java (original)
+++ commons/proper/math/trunk/src/test/java/org/apache/commons/math/random/RandomDataTest.java Sun Feb 12 18:07:53 2012
@@ -45,7 +45,6 @@ import org.apache.commons.math.distribut
import org.apache.commons.math.stat.Frequency;
import org.apache.commons.math.stat.descriptive.SummaryStatistics;
import org.apache.commons.math.stat.inference.ChiSquareTest;
-import org.apache.commons.math.stat.inference.ChiSquareTestImpl;
import org.apache.commons.math.util.FastMath;
import org.apache.commons.math.exception.MathIllegalArgumentException;
import org.junit.Assert;
@@ -73,7 +72,7 @@ public class RandomDataTest {
private final String[] hex = { "0", "1", "2", "3", "4", "5", "6", "7", "8", "9",
"a", "b", "c", "d", "e", "f" };
protected RandomDataImpl randomData = null;
- protected final ChiSquareTestImpl testStatistic = new ChiSquareTestImpl();
+ protected final ChiSquareTest testStatistic = new ChiSquareTest();
@Test
public void testNextIntExtremeValues() {
@@ -473,7 +472,7 @@ public class RandomDataTest {
}
// Use chisquare test to verify that generated values are poisson(mean)-distributed
- ChiSquareTest chiSquareTest = new ChiSquareTestImpl();
+ ChiSquareTest chiSquareTest = new ChiSquareTest();
// Fail if we can reject null hypothesis that distributions are the same
if (chiSquareTest.chiSquareTest(expected, observed, alpha)) {
StringBuilder msgBuffer = new StringBuilder();
Modified: commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/inference/ChiSquareTestTest.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/inference/ChiSquareTestTest.java?rev=1243286&r1=1243285&r2=1243286&view=diff
==============================================================================
--- commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/inference/ChiSquareTestTest.java (original)
+++ commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/inference/ChiSquareTestTest.java Sun Feb 12 18:07:53 2012
@@ -16,7 +16,11 @@
*/
package org.apache.commons.math.stat.inference;
-import org.apache.commons.math.exception.MathIllegalArgumentException;
+import org.apache.commons.math.exception.DimensionMismatchException;
+import org.apache.commons.math.exception.NotPositiveException;
+import org.apache.commons.math.exception.NotStrictlyPositiveException;
+import org.apache.commons.math.exception.OutOfRangeException;
+import org.apache.commons.math.exception.ZeroException;
import org.junit.Assert;
import org.junit.Test;
@@ -29,7 +33,7 @@ import org.junit.Test;
public class ChiSquareTestTest {
- protected UnknownDistributionChiSquareTest testStatistic = new ChiSquareTestImpl();
+ protected ChiSquareTest testStatistic = new ChiSquareTest();
@Test
public void testChiSquare() throws Exception {
@@ -53,8 +57,8 @@ public class ChiSquareTestTest {
try {
testStatistic.chiSquareTest(expected1, observed1, 95);
- Assert.fail("alpha out of range, MathIllegalArgumentException expected");
- } catch (MathIllegalArgumentException ex) {
+ Assert.fail("alpha out of range, OutOfRangeException expected");
+ } catch (OutOfRangeException ex) {
// expected
}
@@ -62,8 +66,8 @@ public class ChiSquareTestTest {
double[] tooShortEx = { 1 };
try {
testStatistic.chiSquare(tooShortEx, tooShortObs);
- Assert.fail("arguments too short, MathIllegalArgumentException expected");
- } catch (MathIllegalArgumentException ex) {
+ Assert.fail("arguments too short, DimensionMismatchException expected");
+ } catch (DimensionMismatchException ex) {
// expected
}
@@ -72,8 +76,8 @@ public class ChiSquareTestTest {
double[] unMatchedEx = { 1, 1, 2 };
try {
testStatistic.chiSquare(unMatchedEx, unMatchedObs);
- Assert.fail("arrays have different lengths, MathIllegalArgumentException expected");
- } catch (MathIllegalArgumentException ex) {
+ Assert.fail("arrays have different lengths, DimensionMismatchException expected");
+ } catch (DimensionMismatchException ex) {
// expected
}
@@ -81,8 +85,8 @@ public class ChiSquareTestTest {
expected[0] = 0;
try {
testStatistic.chiSquareTest(expected, observed, .01);
- Assert.fail("bad expected count, MathIllegalArgumentException expected");
- } catch (MathIllegalArgumentException ex) {
+ Assert.fail("bad expected count, NotStrictlyPositiveException expected");
+ } catch (NotStrictlyPositiveException ex) {
// expected
}
@@ -91,8 +95,8 @@ public class ChiSquareTestTest {
observed[0] = -1;
try {
testStatistic.chiSquareTest(expected, observed, .01);
- Assert.fail("bad expected count, MathIllegalArgumentException expected");
- } catch (MathIllegalArgumentException ex) {
+ Assert.fail("bad expected count, NotPositiveException expected");
+ } catch (NotPositiveException ex) {
// expected
}
@@ -118,8 +122,8 @@ public class ChiSquareTestTest {
long[][] counts3 = { {40, 22, 43}, {91, 21, 28}, {60, 10}};
try {
testStatistic.chiSquare(counts3);
- Assert.fail("Expecting MathIllegalArgumentException");
- } catch (MathIllegalArgumentException ex) {
+ Assert.fail("Expecting DimensionMismatchException");
+ } catch (DimensionMismatchException ex) {
// expected
}
@@ -127,15 +131,15 @@ public class ChiSquareTestTest {
long[][] counts4 = {{40, 22, 43}};
try {
testStatistic.chiSquare(counts4);
- Assert.fail("Expecting MathIllegalArgumentException");
- } catch (MathIllegalArgumentException ex) {
+ Assert.fail("Expecting DimensionMismatchException");
+ } catch (DimensionMismatchException ex) {
// expected
}
long[][] counts5 = {{40}, {40}, {30}, {10}};
try {
testStatistic.chiSquare(counts5);
- Assert.fail("Expecting MathIllegalArgumentException");
- } catch (MathIllegalArgumentException ex) {
+ Assert.fail("Expecting DimensionMismatchException");
+ } catch (DimensionMismatchException ex) {
// expected
}
@@ -143,16 +147,16 @@ public class ChiSquareTestTest {
long[][] counts6 = {{10, -2}, {30, 40}, {60, 90} };
try {
testStatistic.chiSquare(counts6);
- Assert.fail("Expecting MathIllegalArgumentException");
- } catch (MathIllegalArgumentException ex) {
+ Assert.fail("Expecting NotPositiveException");
+ } catch (NotPositiveException ex) {
// expected
}
// bad alpha
try {
testStatistic.chiSquareTest(counts, 0);
- Assert.fail("Expecting MathIllegalArgumentException");
- } catch (MathIllegalArgumentException ex) {
+ Assert.fail("Expecting OutOfRangeException");
+ } catch (OutOfRangeException ex) {
// expected
}
}
@@ -167,8 +171,8 @@ public class ChiSquareTestTest {
long[] obs = new long[] {
2372383, 584222, 257170, 17750155, 7903832, 489265, 209628, 393899
};
- org.apache.commons.math.stat.inference.ChiSquareTestImpl csti =
- new org.apache.commons.math.stat.inference.ChiSquareTestImpl();
+ org.apache.commons.math.stat.inference.ChiSquareTest csti =
+ new org.apache.commons.math.stat.inference.ChiSquareTest();
double cst = csti.chiSquareTest(exp, obs);
Assert.assertEquals("chi-square p-value", 0.0, cst, 1E-3);
Assert.assertEquals( "chi-square test statistic",
@@ -189,7 +193,7 @@ public class ChiSquareTestTest {
/** Target values verified using DATAPLOT version 2006.3 */
@Test
public void testChiSquareDataSetsComparisonEqualCounts()
- throws Exception {
+ throws Exception {
long[] observed1 = {10, 12, 12, 10};
long[] observed2 = {5, 15, 14, 10};
Assert.assertEquals("chi-square p value", 0.541096,
@@ -206,7 +210,7 @@ public class ChiSquareTestTest {
/** Target values verified using DATAPLOT version 2006.3 */
@Test
public void testChiSquareDataSetsComparisonUnEqualCounts()
- throws Exception {
+ throws Exception {
long[] observed1 = {10, 12, 12, 10, 15};
long[] observed2 = {15, 10, 10, 15, 5};
Assert.assertEquals("chi-square p value", 0.124115,
@@ -225,14 +229,14 @@ public class ChiSquareTestTest {
@Test
public void testChiSquareDataSetsComparisonBadCounts()
- throws Exception {
+ throws Exception {
long[] observed1 = {10, -1, 12, 10, 15};
long[] observed2 = {15, 10, 10, 15, 5};
try {
testStatistic.chiSquareTestDataSetsComparison(
observed1, observed2);
- Assert.fail("Expecting MathIllegalArgumentException - negative count");
- } catch (MathIllegalArgumentException ex) {
+ Assert.fail("Expecting NotPositiveException - negative count");
+ } catch (NotPositiveException ex) {
// expected
}
long[] observed3 = {10, 0, 12, 10, 15};
@@ -240,8 +244,8 @@ public class ChiSquareTestTest {
try {
testStatistic.chiSquareTestDataSetsComparison(
observed3, observed4);
- Assert.fail("Expecting MathIllegalArgumentException - double 0's");
- } catch (MathIllegalArgumentException ex) {
+ Assert.fail("Expecting ZeroException - double 0's");
+ } catch (ZeroException ex) {
// expected
}
long[] observed5 = {10, 10, 12, 10, 15};
@@ -249,8 +253,8 @@ public class ChiSquareTestTest {
try {
testStatistic.chiSquareTestDataSetsComparison(
observed5, observed6);
- Assert.fail("Expecting MathIllegalArgumentException - vanishing counts");
- } catch (MathIllegalArgumentException ex) {
+ Assert.fail("Expecting ZeroException - vanishing counts");
+ } catch (ZeroException ex) {
// expected
}
}
Modified: commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/inference/TestUtilsTest.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/inference/TestUtilsTest.java?rev=1243286&r1=1243285&r2=1243286&view=diff
==============================================================================
--- commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/inference/TestUtilsTest.java (original)
+++ commons/proper/math/trunk/src/test/java/org/apache/commons/math/stat/inference/TestUtilsTest.java Sun Feb 12 18:07:53 2012
@@ -19,7 +19,11 @@ package org.apache.commons.math.stat.inf
import java.util.ArrayList;
import java.util.List;
+import org.apache.commons.math.exception.DimensionMismatchException;
import org.apache.commons.math.exception.MathIllegalArgumentException;
+import org.apache.commons.math.exception.NotPositiveException;
+import org.apache.commons.math.exception.NotStrictlyPositiveException;
+import org.apache.commons.math.exception.OutOfRangeException;
import org.apache.commons.math.stat.descriptive.SummaryStatistics;
import org.junit.Assert;
import org.junit.Test;
@@ -54,8 +58,8 @@ public class TestUtilsTest {
try {
TestUtils.chiSquareTest(expected1, observed1, 95);
- Assert.fail("alpha out of range, MathIllegalArgumentException expected");
- } catch (MathIllegalArgumentException ex) {
+ Assert.fail("alpha out of range, OutOfRangeException expected");
+ } catch (OutOfRangeException ex) {
// expected
}
@@ -63,8 +67,8 @@ public class TestUtilsTest {
double[] tooShortEx = { 1 };
try {
TestUtils.chiSquare(tooShortEx, tooShortObs);
- Assert.fail("arguments too short, MathIllegalArgumentException expected");
- } catch (MathIllegalArgumentException ex) {
+ Assert.fail("arguments too short, DimensionMismatchException expected");
+ } catch (DimensionMismatchException ex) {
// expected
}
@@ -73,8 +77,8 @@ public class TestUtilsTest {
double[] unMatchedEx = { 1, 1, 2 };
try {
TestUtils.chiSquare(unMatchedEx, unMatchedObs);
- Assert.fail("arrays have different lengths, MathIllegalArgumentException expected");
- } catch (MathIllegalArgumentException ex) {
+ Assert.fail("arrays have different lengths, DimensionMismatchException expected");
+ } catch (DimensionMismatchException ex) {
// expected
}
@@ -82,8 +86,8 @@ public class TestUtilsTest {
expected[0] = 0;
try {
TestUtils.chiSquareTest(expected, observed, .01);
- Assert.fail("bad expected count, MathIllegalArgumentException expected");
- } catch (MathIllegalArgumentException ex) {
+ Assert.fail("bad expected count, NotStrictlyPositiveException expected");
+ } catch (NotStrictlyPositiveException ex) {
// expected
}
@@ -92,8 +96,8 @@ public class TestUtilsTest {
observed[0] = -1;
try {
TestUtils.chiSquareTest(expected, observed, .01);
- Assert.fail("bad expected count, MathIllegalArgumentException expected");
- } catch (MathIllegalArgumentException ex) {
+ Assert.fail("bad expected count, NotPositiveException expected");
+ } catch (NotPositiveException ex) {
// expected
}
@@ -119,8 +123,8 @@ public class TestUtilsTest {
long[][] counts3 = { {40, 22, 43}, {91, 21, 28}, {60, 10}};
try {
TestUtils.chiSquare(counts3);
- Assert.fail("Expecting MathIllegalArgumentException");
- } catch (MathIllegalArgumentException ex) {
+ Assert.fail("Expecting DimensionMismatchException");
+ } catch (DimensionMismatchException ex) {
// expected
}
@@ -128,15 +132,15 @@ public class TestUtilsTest {
long[][] counts4 = {{40, 22, 43}};
try {
TestUtils.chiSquare(counts4);
- Assert.fail("Expecting MathIllegalArgumentException");
- } catch (MathIllegalArgumentException ex) {
+ Assert.fail("Expecting DimensionMismatchException");
+ } catch (DimensionMismatchException ex) {
// expected
}
long[][] counts5 = {{40}, {40}, {30}, {10}};
try {
TestUtils.chiSquare(counts5);
- Assert.fail("Expecting MathIllegalArgumentException");
- } catch (MathIllegalArgumentException ex) {
+ Assert.fail("Expecting DimensionMismatchException");
+ } catch (DimensionMismatchException ex) {
// expected
}
@@ -144,16 +148,16 @@ public class TestUtilsTest {
long[][] counts6 = {{10, -2}, {30, 40}, {60, 90} };
try {
TestUtils.chiSquare(counts6);
- Assert.fail("Expecting MathIllegalArgumentException");
- } catch (MathIllegalArgumentException ex) {
+ Assert.fail("Expecting NotPositiveException");
+ } catch (NotPositiveException ex) {
// expected
}
// bad alpha
try {
TestUtils.chiSquareTest(counts, 0);
- Assert.fail("Expecting MathIllegalArgumentException");
- } catch (MathIllegalArgumentException ex) {
+ Assert.fail("Expecting OutOfRangeException");
+ } catch (OutOfRangeException ex) {
// expected
}
}
@@ -168,8 +172,8 @@ public class TestUtilsTest {
long[] obs = new long[] {
2372383, 584222, 257170, 17750155, 7903832, 489265, 209628, 393899
};
- org.apache.commons.math.stat.inference.ChiSquareTestImpl csti =
- new org.apache.commons.math.stat.inference.ChiSquareTestImpl();
+ org.apache.commons.math.stat.inference.ChiSquareTest csti =
+ new org.apache.commons.math.stat.inference.ChiSquareTest();
double cst = csti.chiSquareTest(exp, obs);
Assert.assertEquals("chi-square p-value", 0.0, cst, 1E-3);
Assert.assertEquals( "chi-square test statistic",