| Function |
Purpose
Statement |
| canonicalCorrelation |
Given an input
array of deviate
values, generates a
canonical
correlation array. |
| categoricalGlm |
Analyzes
categorical data
using logistic,
Probit, Poisson,
and other
generalized linear
models. |
| chiSquaredCdf |
Evaluates the
chi-squared
distribution
function. |
| chiSquaredInverseCdf |
Evaluates the
inverse of the
chi-squared
distribution
function. |
| chiSquaredNormalityTest |
Performs a
chi-squared test
for normality. |
| chiSquaredTest |
Performs a
chi-squared
goodness-of-fit
test. |
| clusterHierarchical |
Performs a
hierarchical
cluster analysis
given a distance
matrix. |
| clusterKMeans |
Performs a
K-means
(centroid) cluster
analysis. |
| clusterNumber |
Computes cluster
membership for a
hierarchical
cluster tree. |
| cochranQTest |
Performs a Cochran
Q test for
related
observations. |
| complementaryChiSquaredCdf |
Calculates the
complement of the
chi-squared
distribution. |
| complementaryFCdf |
Calculates the
complement of the
F distribution
function. |
| complementaryNonCentralFCdf |
Evaluates the
complementary
noncentral F
cumulative
distribution
function (CDF). |
| complementaryTCdf |
Calculates the
complement of the
Student’s t
distribution
function. |
| contingencyTable |
Performs a
chi-squared
analysis of a
two-way contingency
table. |
| continuousTableSetup |
Sets up a table to
generate
pseudorandom
numbers from a
general continuous
distribution. |
| covariances |
Computes the sample
variance-covariance
or correlation
matrix. |
| coxStuartTrendsTest |
Performs the Cox
and Stuart’ sign
test for trends in
location and
dispersion. |
| crdFactorial |
Analyzes data from
balanced and
unbalanced
completely
randomized
experiments. |
| crosscorrelation |
Computes the sample
cross-correlation
function of two
stationary time
series. |
| cvmNormalityTest |
Performs a
Cramer-von-Mises
test for normality. |