# 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. 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. 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.