Descriptive statistics and computation#

Descriptive statistics#

aggregate

Aggregates the data in the columns of a matrix based upon a column containing group ids with a choice of method.

dstatmt

Computes descriptive statistics of a dataset, dataframe, or matrix.

frequency

Generate frequency table.

JarqueBera

Computes the Jarque-Bera goodness-of-fit test

kurtosis

Computes the sample kurtosis.

maxc

Computes maximum value of each column of a matrix.

meanc

Computes mean value of each column of a matrix.

median

Computes medians of the columns of a matrix.

minc

Computes minimum value of each column of a matrix.

modec

Computes mode of each column of a matrix.

quantile

Computes quantiles from each column in a matrix, given specified probabilities.

../skew

Computes the sample skew.

stdc

Computes the sample standard deviation of the elements in each column of a matrix.

tabulate

Computes and returns two-way tables of frequencies.

vcm, vcx

Computes an unbiased estimate of a variance-covariance matrix from a matrix \(x\) or a moment matrix, \(x'x\).

Computation#

cumprodc

Computes the cumulative products of the columns of a matrix.

cumsumc

Computes the cumulative sums of the columns of a matrix.

prodc

Computes the products of all elements in each column of a matrix.

prodr

Computes the products of all elements in each row of a matrix.

sumc

Computes the sum of each column of a matrix or the sum across the second-fastest moving dimension of an L-dimensional array.

sumr

Computes the sum of each row of a matrix or the sum of the fastest moving dimension of an L-dimensional array.

maxindc

Returns a column vector containing the index (i.e., row number) of the maximum element in each column of a matrix.

minindc

Returns a column vector containing the index (i.e., row number) of the smallest element in each column of a matrix.