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Posted to commits@commons.apache.org by mi...@apache.org on 2011/03/21 10:39:24 UTC
svn commit: r1083716 - in /commons/proper/math/trunk/src:
main/java/org/apache/commons/math/distribution/ test/R/
test/java/org/apache/commons/math/distribution/
Author: mikl
Date: Mon Mar 21 09:39:23 2011
New Revision: 1083716
URL: http://svn.apache.org/viewvc?rev=1083716&view=rev
Log:
Fixes MATH-437
Added:
commons/proper/math/trunk/src/main/java/org/apache/commons/math/distribution/KolmogorovSmirnovDistribution.java (with props)
commons/proper/math/trunk/src/main/java/org/apache/commons/math/distribution/KolmogorovSmirnovDistributionImpl.java (with props)
commons/proper/math/trunk/src/test/R/KolmogorovSmirnovDistributionTestCases.R
commons/proper/math/trunk/src/test/java/org/apache/commons/math/distribution/KolmogorovSmirnovDistributionTest.java (with props)
Added: commons/proper/math/trunk/src/main/java/org/apache/commons/math/distribution/KolmogorovSmirnovDistribution.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/main/java/org/apache/commons/math/distribution/KolmogorovSmirnovDistribution.java?rev=1083716&view=auto
==============================================================================
--- commons/proper/math/trunk/src/main/java/org/apache/commons/math/distribution/KolmogorovSmirnovDistribution.java (added)
+++ commons/proper/math/trunk/src/main/java/org/apache/commons/math/distribution/KolmogorovSmirnovDistribution.java Mon Mar 21 09:39:23 2011
@@ -0,0 +1,56 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.commons.math.distribution;
+
+/**
+ * Treats the distribution of the two-sided
+ * {@code P(D<sub>n</sup> < d)}
+ * where {@code D<sub>n</sup> = sup_x | G(x) - Gn (x) |} for the
+ * theoretical cdf G and the emperical cdf Gn.
+ *
+ * This implementation is based on [1] with certain quick
+ * decisions for extreme values given in [2].
+ *
+ * In short, when wanting to evaluate {@code P(D<sub>n</sup> < d)},
+ * the method in [1] is to write {@code d = (k - h) / n} for positive
+ * integer {@code k} and {@code 0 <= h < 1}. Then
+ * {@code P(D<sub>n</sup> < d) = (n!/n^n) * t_kk}
+ * where {@code t_kk} is the (k, k)'th entry in the special matrix {@code H^n},
+ * i.e. {@code H} to the {@code n}'th power.
+ *
+ * See also <a href="http://en.wikipedia.org/wiki/Kolmogorov-Smirnov_test">
+ * Kolmogorov-Smirnov test on Wikipedia</a> for details.
+ *
+ * References:
+ * [1] Evaluating Kolmogorov's Distribution by George Marsaglia, Wai
+ * Wan Tsang, Jingbo Wang http://www.jstatsoft.org/v08/i18/paper
+ *
+ * [2] <a href="http://www.iro.umontreal.ca/~lecuyer/myftp/papers/ksdist.pdf">
+ * Computing the Two-Sided Kolmogorov-Smirnov Distribution</a> by Richard Simard
+ * and Pierre L'Ecuyer
+ *
+ * Note that [1] contains an error in computing h, refer to
+ * <a href="https://issues.apache.org/jira/browse/MATH-437">MATH-437</a> for details.
+ *
+ * @version $Revision$ $Date$
+ */
+public interface KolmogorovSmirnovDistribution {
+
+ public double cdf(double d);
+
+}
Propchange: commons/proper/math/trunk/src/main/java/org/apache/commons/math/distribution/KolmogorovSmirnovDistribution.java
------------------------------------------------------------------------------
svn:eol-style = native
Propchange: commons/proper/math/trunk/src/main/java/org/apache/commons/math/distribution/KolmogorovSmirnovDistribution.java
------------------------------------------------------------------------------
svn:keywords = Author Date Id Revision
Added: commons/proper/math/trunk/src/main/java/org/apache/commons/math/distribution/KolmogorovSmirnovDistributionImpl.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/main/java/org/apache/commons/math/distribution/KolmogorovSmirnovDistributionImpl.java?rev=1083716&view=auto
==============================================================================
--- commons/proper/math/trunk/src/main/java/org/apache/commons/math/distribution/KolmogorovSmirnovDistributionImpl.java (added)
+++ commons/proper/math/trunk/src/main/java/org/apache/commons/math/distribution/KolmogorovSmirnovDistributionImpl.java Mon Mar 21 09:39:23 2011
@@ -0,0 +1,328 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.commons.math.distribution;
+
+import java.io.Serializable;
+import java.math.BigDecimal;
+
+import org.apache.commons.math.exception.MathArithmeticException;
+import org.apache.commons.math.exception.NotStrictlyPositiveException;
+import org.apache.commons.math.exception.util.LocalizedFormats;
+import org.apache.commons.math.fraction.BigFraction;
+import org.apache.commons.math.fraction.FractionConversionException;
+import org.apache.commons.math.linear.Array2DRowFieldMatrix;
+import org.apache.commons.math.linear.Array2DRowRealMatrix;
+import org.apache.commons.math.linear.FieldMatrix;
+import org.apache.commons.math.linear.RealMatrix;
+
+/**
+ * The default implementation of {@link KolmogorovSmirnovDistribution}.
+ *
+ * @version $Revision$ $Date$
+ */
+public class KolmogorovSmirnovDistributionImpl implements KolmogorovSmirnovDistribution, Serializable {
+
+ /** Serializable version identifier. */
+ private static final long serialVersionUID = -4670676796862967187L;
+
+ private int n;
+
+ /**
+ * @param n Number of observations
+ * @throws NotStrictlyPositiveException
+ * if n <= 0
+ */
+ public KolmogorovSmirnovDistributionImpl(int n) {
+ if (n <= 0) {
+ throw new NotStrictlyPositiveException(LocalizedFormats.NOT_POSITIVE_NUMBER_OF_SAMPLES, n);
+ }
+
+ this.n = n;
+ }
+
+ /**
+ * Calculates {@code P(D<sub>n</sup> < d)} using method described in
+ * [1] with quick decisions for extreme values given in [2] (see above). The
+ * result is not exact as with
+ * {@link KolmogorovSmirnovDistributionImpl#cdfExact(double)} because
+ * calculations are based on double rather than
+ * {@link org.apache.commons.math.fraction.BigFraction}.
+ *
+ * @param d statistic
+ * @return the two-sided probability of {@code P(D<sub>n</sup> < d)}
+ * @throws MathArithmeticException
+ * if algorithm fails to convert h to a BigFraction in
+ * expressing d as (k - h) / m for integer k, m and 0 <= h < 1.
+ */
+ @Override
+ public double cdf(double d) throws MathArithmeticException {
+ return this.cdf(d, false);
+ }
+
+ /**
+ * Calculates {@code P(D<sub>n</sup> < d)} using method described in
+ * [1] with quick decisions for extreme values given in [2] (see above).
+ * The result is exact in the sense that BigFraction/BigReal is used everywhere
+ * at the expense of very slow execution time. Almost never choose this in
+ * real applications unless you are very sure; this is almost solely for
+ * verification purposes. Normally, you would choose
+ * {@link KolmogorovSmirnovDistributionImpl#cdf(double)}
+ *
+ * @param d statistic
+ * @return the two-sided probability of {@code P(D<sub>n</sup> < d)}
+ * @throws MathArithmeticException
+ * if algorithm fails to convert h to a BigFraction in
+ * expressing d as (k - h) / m for integer k, m and 0 <= h < 1.
+ */
+ public double cdfExact(double d) throws MathArithmeticException {
+ return this.cdf(d, true);
+ }
+
+ /**
+ * Calculates {@code P(D<sub>n</sup> < d)} using method described in
+ * [1] with quick decisions for extreme values given in [2] (see above).
+ *
+ * @param d statistic
+ * @param exact
+ * whether the probability should be calculated exact using
+ * BigFraction everywhere at the expense of very
+ * slow execution time, or if double should be used convenient
+ * places to gain speed. Never choose true in real applications
+ * unless you are very sure; true is almost solely for
+ * verification purposes.
+ * @return the two-sided probability of {@code P(D<sub>n</sup> < d)}
+ * @throws MathArithmeticException
+ * if algorithm fails to convert h to a BigFraction in
+ * expressing d as (k - h) / m for integer k, m and 0 <= h < 1.
+ */
+ public double cdf(double d, boolean exact)
+ throws MathArithmeticException {
+
+ final int n = this.n;
+
+ final double ninv = 1 / ((double) n);
+ final double ninvhalf = 0.5 * ninv;
+
+ if (d <= ninvhalf) {
+
+ return 0;
+
+ } else if (ninvhalf < d && d <= ninv) {
+
+ double res = 1;
+ double f = 2 * d - ninv;
+
+ // n! f^n = n*f * (n-1)*f * ... * 1*x
+ for (int i = 1; i <= n; ++i) {
+ res *= i * f;
+ }
+
+ return res;
+
+ } else if (1 - ninv <= d && d < 1) {
+
+ return 1 - 2 * Math.pow(1 - d, n);
+
+ } else if (1 <= d) {
+
+ return 1;
+ }
+
+ return (exact) ? this.exactK(d) : this.roundedK(d);
+ }
+
+ /**
+ * Calculates {@code P(D<sub>n</sup> < d)} exact using method
+ * described in [1] and BigFraction (see above).
+ *
+ * @param d statistic
+ * @return the two-sided probability of {@code P(D<sub>n</sup> < d)}
+ * @throws MathArithmeticException
+ * if algorithm fails to convert h to a BigFraction in
+ * expressing d as (k - h) / m for integer k, m and 0 <= h < 1.
+ */
+ private double exactK(double d)
+ throws MathArithmeticException {
+
+ final int n = this.n;
+ final int k = (int) Math.ceil(n * d);
+
+ final FieldMatrix<BigFraction> H = this.createH(d);
+ final FieldMatrix<BigFraction> Hpower = H.power(n);
+
+ BigFraction pFrac = Hpower.getEntry(k - 1, k - 1);
+
+ for (int i = 1; i <= n; ++i) {
+ pFrac = pFrac.multiply(i).divide(n);
+ }
+
+ /*
+ * BigFraction.doubleValue converts numerator to double and the
+ * denominator to double and divides afterwards. That gives NaN quite
+ * easy. This does not (scale is the number of digits):
+ */
+ return pFrac.bigDecimalValue(20, BigDecimal.ROUND_HALF_UP)
+ .doubleValue();
+ }
+
+ /**
+ * Calculates <code>P(D<sub>n</sup> < d)</code> using method described in
+ * [1] and doubles (see above).
+ *
+ * @param d statistic
+ * @return the two-sided probability of {@code P(D<sub>n</sup> < d)}
+ * @throws MathArithmeticException
+ * if algorithm fails to convert h to a BigFraction in
+ * expressing d as (k - h) / m for integer k, m and 0 <= h < 1.
+ */
+ private double roundedK(double d)
+ throws MathArithmeticException {
+
+ final int n = this.n;
+ final int k = (int) Math.ceil(n * d);
+ final FieldMatrix<BigFraction> HBigFraction = this.createH(d);
+ final int m = HBigFraction.getRowDimension();
+
+ /*
+ * Here the rounding part comes into play: use
+ * RealMatrix instead of FieldMatrix<BigFraction>
+ */
+ final RealMatrix H = new Array2DRowRealMatrix(m, m);
+
+ for (int i = 0; i < m; ++i) {
+ for (int j = 0; j < m; ++j) {
+ H.setEntry(i, j, HBigFraction.getEntry(i, j).doubleValue());
+ }
+ }
+
+ final RealMatrix Hpower = H.power(n);
+
+ double pFrac = Hpower.getEntry(k - 1, k - 1);
+
+ for (int i = 1; i <= n; ++i) {
+ pFrac *= (double)i / (double)n;
+ }
+
+ return pFrac;
+ }
+
+ /***
+ * Creates H of size m x m as described in [1] (see above).
+ *
+ * @param d statistic
+ *
+ * @throws MathArithmeticException
+ * if algorithm fails to convert h to a BigFraction in
+ * expressing x as (k - h) / m for integer k, m and 0 <= h < 1.
+ */
+ private FieldMatrix<BigFraction> createH(double d)
+ throws MathArithmeticException {
+
+ int n = this.n;
+ int k = (int) Math.ceil(n * d);
+
+ int m = 2 * k - 1;
+ double hDouble = k - n * d;
+
+ if (hDouble >= 1) {
+ throw new ArithmeticException("Could not ");
+ }
+
+ BigFraction h = null;
+
+ try {
+ h = new BigFraction(hDouble, 1.0e-20, 10000);
+ } catch (FractionConversionException e1) {
+ try {
+ h = new BigFraction(hDouble, 1.0e-10, 10000);
+ } catch (FractionConversionException e2) {
+ try {
+ h = new BigFraction(hDouble, 1.0e-5, 10000);
+ } catch (FractionConversionException e3) {
+ //throw new MathArithmeticException(hDouble, 10000);
+ throw new MathArithmeticException(LocalizedFormats.CANNOT_CONVERT_OBJECT_TO_FRACTION, hDouble);
+ }
+ }
+ }
+
+ final BigFraction[][] Hdata = new BigFraction[m][m];
+
+ /*
+ * Start by filling everything with either 0 or 1.
+ */
+ for (int i = 0; i < m; ++i) {
+ for (int j = 0; j < m; ++j) {
+ if (i - j + 1 < 0)
+ Hdata[i][j] = BigFraction.ZERO;
+ else
+ Hdata[i][j] = BigFraction.ONE;
+ }
+ }
+
+ /*
+ * Setting up power-array to avoid calculating the same value twice:
+ * hPowers[0] = h^1 ... hPowers[m-1] = h^m
+ */
+ final BigFraction[] hPowers = new BigFraction[m];
+ hPowers[0] = h;
+ for (int i = 1; i < m; ++i) {
+ hPowers[i] = h.multiply(hPowers[i - 1]);
+ }
+
+ /*
+ * First column and last row has special values (each other reversed).
+ */
+ for (int i = 0; i < m; ++i) {
+ Hdata[i][0] = Hdata[i][0].subtract(hPowers[i]);
+ Hdata[m - 1][i] = Hdata[m - 1][i].subtract(hPowers[m - i - 1]);
+ }
+
+ /*
+ * [1] states: "For 1/2 < h < 1 the bottom left element of the matrix
+ * should be (1 - 2*h^m + (2h - 1)^m )/m!" Since 0 <= h < 1, then if h >
+ * 1/2 is sufficient to check:
+ */
+ if (h.compareTo(BigFraction.ONE_HALF) == 1) {
+ Hdata[m - 1][0] = Hdata[m - 1][0].add(h.multiply(2).subtract(1)
+ .pow(m));
+ }
+
+ /*
+ * Aside from the first column and last row, the (i, j)-th element is
+ * 1/(i - j + 1)! if i â j + 1 >= 0, else 0. 1's and 0's are already
+ * put, so only division with (i - j + 1)! is needed in the elements
+ * that have 1's. There is no need to calculate (i - j + 1)! and then
+ * divide - small steps avoid overflows.
+ *
+ * Note that i - j + 1 > 0 <=> i + 1 > j instead of j'ing all the way to
+ * m. Also note that it is started at g = 2 because dividing by 1 isn't
+ * really necessary.
+ */
+ for (int i = 0; i < m; ++i) {
+ for (int j = 0; j < i + 1; ++j) {
+ if (i - j + 1 > 0) {
+ for (int g = 2; g <= i - j + 1; ++g) {
+ Hdata[i][j] = Hdata[i][j].divide(g);
+ }
+ }
+ }
+ }
+
+ return new Array2DRowFieldMatrix<BigFraction>(Hdata);
+ }
+}
Propchange: commons/proper/math/trunk/src/main/java/org/apache/commons/math/distribution/KolmogorovSmirnovDistributionImpl.java
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svn:eol-style = native
Propchange: commons/proper/math/trunk/src/main/java/org/apache/commons/math/distribution/KolmogorovSmirnovDistributionImpl.java
------------------------------------------------------------------------------
svn:keywords = Author Date Id Revision
Added: commons/proper/math/trunk/src/test/R/KolmogorovSmirnovDistributionTestCases.R
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/test/R/KolmogorovSmirnovDistributionTestCases.R?rev=1083716&view=auto
==============================================================================
--- commons/proper/math/trunk/src/test/R/KolmogorovSmirnovDistributionTestCases.R (added)
+++ commons/proper/math/trunk/src/test/R/KolmogorovSmirnovDistributionTestCases.R Mon Mar 21 09:39:23 2011
@@ -0,0 +1,22 @@
+cat("/* ", version$version.string, " */\n\n\n", sep = "")
+
+ns <- c(200, 341, 389)
+ps <- c(0.005, 0.02, 0.031111, 0.04)
+
+for (n in ns) {
+ for (p in ps) {
+ res <- .C("pkolmogorov2x", p = as.double(p), n = as.integer(n), PACKAGE = "stats")$p
+
+ cat("/* formatC(.C(\"pkolmogorov2x\", p = as.double(", p, "), n = as.integer(", n, "), PACKAGE = \"stats\")$p, 40) gives\n", sep = "")
+ cat(" * ", formatC(res, digits = 40), "\n", sep = "")
+ cat(" */\n")
+
+ cat("dist = new KolmogorovSmirnovDistributionImpl(", n, ");\n", sep = "")
+ #cat("assertEquals(", formatC(res, digits = 40), ", dist.cdf(", p, ", true), TOLERANCE);\n", sep = "")
+ cat("assertEquals(", formatC(res, digits = 40), ", dist.cdf(", p, ", false), TOLERANCE);\n", sep = "")
+ cat("\n")
+
+ #cat("System.out.println(\"", formatC(res, digits = 20), " - \" + dist.cdf(", p, ", false) + \" = \" + (", res, " - dist.cdf(", p, ", false)));\n", sep = "")
+ }
+}
+
Added: commons/proper/math/trunk/src/test/java/org/apache/commons/math/distribution/KolmogorovSmirnovDistributionTest.java
URL: http://svn.apache.org/viewvc/commons/proper/math/trunk/src/test/java/org/apache/commons/math/distribution/KolmogorovSmirnovDistributionTest.java?rev=1083716&view=auto
==============================================================================
--- commons/proper/math/trunk/src/test/java/org/apache/commons/math/distribution/KolmogorovSmirnovDistributionTest.java (added)
+++ commons/proper/math/trunk/src/test/java/org/apache/commons/math/distribution/KolmogorovSmirnovDistributionTest.java Mon Mar 21 09:39:23 2011
@@ -0,0 +1,116 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.commons.math.distribution;
+
+import junit.framework.TestCase;
+
+/**
+ * Test cases for {@link KolmogorovSmirnovDistributionImpl}.
+ *
+ * @version $Revision$ $Date$
+ */
+public class KolmogorovSmirnovDistributionTest extends TestCase {
+
+ private static final double TOLERANCE = 10e-10;
+
+ public void testCumulativeDensityFunction() throws Exception {
+
+ KolmogorovSmirnovDistributionImpl dist;
+
+ /* The code below is generated using the R-script located in
+ * /src/test/R/KolmogorovSmirnovDistributionTestCases.R
+ */
+
+ /* R version 2.11.1 (2010-05-31) */
+
+
+ /* formatC(.C("pkolmogorov2x", p = as.double(0.005), n = as.integer(200), PACKAGE = "stats")$p, 40) gives
+ * 4.907829957616471622388047046469198862537e-86
+ */
+ dist = new KolmogorovSmirnovDistributionImpl(200);
+ assertEquals(4.907829957616471622388047046469198862537e-86, dist.cdf(0.005, false), TOLERANCE);
+
+ /* formatC(.C("pkolmogorov2x", p = as.double(0.02), n = as.integer(200), PACKAGE = "stats")$p, 40) gives
+ * 5.151982014280041957199687829849210629618e-06
+ */
+ dist = new KolmogorovSmirnovDistributionImpl(200);
+ assertEquals(5.151982014280041957199687829849210629618e-06, dist.cdf(0.02, false), TOLERANCE);
+
+ /* formatC(.C("pkolmogorov2x", p = as.double(0.031111), n = as.integer(200), PACKAGE = "stats")$p, 40) gives
+ * 0.01291614648162886340443389343590752105229
+ */
+ dist = new KolmogorovSmirnovDistributionImpl(200);
+ assertEquals(0.01291614648162886340443389343590752105229, dist.cdf(0.031111, false), TOLERANCE);
+
+ /* formatC(.C("pkolmogorov2x", p = as.double(0.04), n = as.integer(200), PACKAGE = "stats")$p, 40) gives
+ * 0.1067137011362679355208626930107129737735
+ */
+ dist = new KolmogorovSmirnovDistributionImpl(200);
+ assertEquals(0.1067137011362679355208626930107129737735, dist.cdf(0.04, false), TOLERANCE);
+
+ /* formatC(.C("pkolmogorov2x", p = as.double(0.005), n = as.integer(341), PACKAGE = "stats")$p, 40) gives
+ * 1.914734701559404553985102395145063418825e-53
+ */
+ dist = new KolmogorovSmirnovDistributionImpl(341);
+ assertEquals(1.914734701559404553985102395145063418825e-53, dist.cdf(0.005, false), TOLERANCE);
+
+ /* formatC(.C("pkolmogorov2x", p = as.double(0.02), n = as.integer(341), PACKAGE = "stats")$p, 40) gives
+ * 0.001171328985781981343872182321774744195864
+ */
+ dist = new KolmogorovSmirnovDistributionImpl(341);
+ assertEquals(0.001171328985781981343872182321774744195864, dist.cdf(0.02, false), TOLERANCE);
+
+ /* formatC(.C("pkolmogorov2x", p = as.double(0.031111), n = as.integer(341), PACKAGE = "stats")$p, 40) gives
+ * 0.1142955196267499418105728636874118819833
+ */
+ dist = new KolmogorovSmirnovDistributionImpl(341);
+ assertEquals(0.1142955196267499418105728636874118819833, dist.cdf(0.031111, false), TOLERANCE);
+
+ /* formatC(.C("pkolmogorov2x", p = as.double(0.04), n = as.integer(341), PACKAGE = "stats")$p, 40) gives
+ * 0.3685529520496805266915885113121476024389
+ */
+ dist = new KolmogorovSmirnovDistributionImpl(341);
+ assertEquals(0.3685529520496805266915885113121476024389, dist.cdf(0.04, false), TOLERANCE);
+
+ /* formatC(.C("pkolmogorov2x", p = as.double(0.005), n = as.integer(389), PACKAGE = "stats")$p, 40) gives
+ * 1.810657144595055888918455512707637574637e-47
+ */
+ dist = new KolmogorovSmirnovDistributionImpl(389);
+ assertEquals(1.810657144595055888918455512707637574637e-47, dist.cdf(0.005, false), TOLERANCE);
+
+ /* formatC(.C("pkolmogorov2x", p = as.double(0.02), n = as.integer(389), PACKAGE = "stats")$p, 40) gives
+ * 0.003068542559702356568168690742481885536108
+ */
+ dist = new KolmogorovSmirnovDistributionImpl(389);
+ assertEquals(0.003068542559702356568168690742481885536108, dist.cdf(0.02, false), TOLERANCE);
+
+ /* formatC(.C("pkolmogorov2x", p = as.double(0.031111), n = as.integer(389), PACKAGE = "stats")$p, 40) gives
+ * 0.1658291700122746237244797384846606291831
+ */
+ dist = new KolmogorovSmirnovDistributionImpl(389);
+ assertEquals(0.1658291700122746237244797384846606291831, dist.cdf(0.031111, false), TOLERANCE);
+
+ /* formatC(.C("pkolmogorov2x", p = as.double(0.04), n = as.integer(389), PACKAGE = "stats")$p, 40) gives
+ * 0.4513143712128902529379104180407011881471
+ */
+ dist = new KolmogorovSmirnovDistributionImpl(389);
+ assertEquals(0.4513143712128902529379104180407011881471, dist.cdf(0.04, false), TOLERANCE);
+
+ }
+
+}
Propchange: commons/proper/math/trunk/src/test/java/org/apache/commons/math/distribution/KolmogorovSmirnovDistributionTest.java
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Propchange: commons/proper/math/trunk/src/test/java/org/apache/commons/math/distribution/KolmogorovSmirnovDistributionTest.java
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svn:keywords = Author Date Id Revision