 center | % If @var{x} is a vector, subtract its mean. |
| cloglog | % Return the complementary log-log function of @var{x}, defined as |
| cor | % Compute correlation. |
| corrcoef | % Compute correlation. |
| cov | % Compute covariance. |
| cut | % Create categorical data out of numerical or continuous data by |
| gls | % Generalized least squares estimation for the multivariate model |
| histc | % Produce histogram counts. |
| iqr | % If @var{x} is a vector, return the interquartile range, i.e., the |
| kendall | % Compute Kendall's @var{tau} for each of the variables specified by |
| kurtosis | % If @var{x} is a vector of length @math{N}, return the kurtosis |
| logit | % For each component of @var{p}, return the logit of @var{p} defined as |
| mahalanobis | % Return the Mahalanobis' D-square distance between the multivariate |
| mean | % If @var{x} is a vector, compute the mean of the elements of @var{x} |
| meansq | % For vector arguments, return the mean square of the values. |
| median | % If @var{x} is a vector, compute the median value of the elements of |
| mode | % Count the most frequently appearing value. @code{mode} counts the |
| moment | % If @var{x} is a vector, compute the @var{p}-th moment of @var{x}. |
| ols | % Ordinary least squares estimation for the multivariate model |
| ppplot | % Perform a PP-plot (probability plot). |
| prctile | % For a sample @var{x}, compute the quantiles, @var{y}, corresponding |
| probit | % For each component of @var{p}, return the probit (the quantile of the |
| qqplot | % Perform a QQ-plot (quantile plot). |
| quantile | % For a sample, @var{x}, calculate the quantiles, @var{q}, corresponding to |
| range | % If @var{x} is a vector, return the range, i.e., the difference |
| ranks | % Return the ranks of @var{x} along the first non-singleton dimension |
| run_count | % Count the upward runs along the first non-singleton dimension of |
| skewness | % If @var{x} is a vector of length @math{n}, return the skewness |
| spearman | % Compute Spearman's rank correlation coefficient @var{rho} for each of |
| statistics | % If @var{x} is a matrix, return a matrix with the minimum, first |
| std | % If @var{x} is a vector, compute the standard deviation of the elements |
| studentize | % If @var{x} is a vector, subtract its mean and divide by its standard |
| table | % Create a contingency table @var{t} from data vectors. The @var{l} |
| values | % Return the different values in a column vector, arranged in ascending |
| var | % For vector arguments, return the (real) variance of the values. |
Master index