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Index for ./freetb4matlab/statistics/base

Matlab files in this directory:

 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.

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