You are viewing a plain text version of this content. The canonical link for it is here.
Posted to commits@systemml.apache.org by gw...@apache.org on 2017/10/10 17:48:08 UTC
systemml git commit: [MINOR][DOC] Update description of statistical
built-in functions sd and var
Repository: systemml
Updated Branches:
refs/heads/master be3e0c993 -> 31bbeb5b2
[MINOR][DOC] Update description of statistical built-in functions sd and var
Project: http://git-wip-us.apache.org/repos/asf/systemml/repo
Commit: http://git-wip-us.apache.org/repos/asf/systemml/commit/31bbeb5b
Tree: http://git-wip-us.apache.org/repos/asf/systemml/tree/31bbeb5b
Diff: http://git-wip-us.apache.org/repos/asf/systemml/diff/31bbeb5b
Branch: refs/heads/master
Commit: 31bbeb5b27359bdff387b5b5a202418344feb720
Parents: be3e0c9
Author: Glenn Weidner <gw...@us.ibm.com>
Authored: Tue Oct 10 10:46:00 2017 -0700
Committer: Glenn Weidner <gw...@us.ibm.com>
Committed: Tue Oct 10 10:46:00 2017 -0700
----------------------------------------------------------------------
docs/dml-language-reference.md | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
----------------------------------------------------------------------
http://git-wip-us.apache.org/repos/asf/systemml/blob/31bbeb5b/docs/dml-language-reference.md
----------------------------------------------------------------------
diff --git a/docs/dml-language-reference.md b/docs/dml-language-reference.md
index 58ca306..e377596 100644
--- a/docs/dml-language-reference.md
+++ b/docs/dml-language-reference.md
@@ -683,7 +683,7 @@ as.double(), <br/> as.integer(), <br/> as.logical() | A variable is cast as the
Function | Description | Parameters | Example
-------- | ----------- | ---------- | -------
mean() <br/> avg() | Return the mean value of all cells in matrix | Input: matrix <br/> Output: scalar | mean(X)
-var() <br/> sd() | Return the variance/stdDev value of all cells in matrix | Input: matrix <br/> Output: scalar | var(X) <br/> sd(X)
+var() <br/> sd() | Return the variance/stdDev value of all cells in matrix. Both use unbiased estimators with (n-1) denominator. | Input: matrix <br/> Output: scalar | var(X) <br/> sd(X)
moment() | Returns the kth central moment of values in a column matrix V, where k = 2, 3, or 4. It can be used to compute statistical measures like Variance, Kurtosis, and Skewness. This function also takes an optional weights parameter W. | Input: (X <(n x 1) matrix>, [W <(n x 1) matrix>),] k <scalar>) <br/> Output: <scalar> | A = rand(rows=100000,cols=1, pdf="normal") <br/> print("Variance from our (standard normal) random generator is approximately " + moment(A,2))
colSums() <br/> colMeans() <br/> colVars() <br/> colSds() <br/> colMaxs() <br/> colMins() | Column-wise computations -- for each column, compute the sum/mean/variance/stdDev/max/min of cell values | Input: matrix <br/> Output: (1 x n) matrix | colSums(X) <br/> colMeans(X) <br/> colVars(X) <br/> colSds(X) <br/> colMaxs(X) <br/>colMins(X)
cov() | Returns the covariance between two 1-dimensional column matrices X and Y. The function takes an optional weights parameter W. All column matrices X, Y, and W (when specified) must have the exact same dimension. | Input: (X <(n x 1) matrix>, Y <(n x 1) matrix> [, W <(n x 1) matrix>)]) <br/> Output: <scalar> | cov(X,Y) <br/> cov(X,Y,W)