mars.tensor.amin
Return the minimum of a tensor or minimum along an axis.
mars.tensor.amax
Return the maximum of an array or maximum along an axis.
mars.tensor.nanmin
Return minimum of a tensor or minimum along an axis, ignoring any NaNs.
mars.tensor.nanmax
Return the maximum of an array or maximum along an axis, ignoring any NaNs.
mars.tensor.ptp
Range of values (maximum - minimum) along an axis.
mars.tensor.average
Compute the weighted average along the specified axis.
mars.tensor.mean
Compute the arithmetic mean along the specified axis.
mars.tensor.std
Compute the standard deviation along the specified axis.
mars.tensor.var
Compute the variance along the specified axis.
mars.tensor.nanmean
Compute the arithmetic mean along the specified axis, ignoring NaNs.
mars.tensor.nanstd
Compute the standard deviation along the specified axis, while ignoring NaNs.
mars.tensor.nanvar
Compute the variance along the specified axis, while ignoring NaNs.
mars.tensor.corrcoef
Return Pearson product-moment correlation coefficients.
mars.tensor.cov
Estimate a covariance matrix, given data and weights.
mars.tensor.histogram
Compute the histogram of a set of data.
mars.tensor.histogram_bin_edges
Function to calculate only the edges of the bins used by the histogram function.
mars.tensor.digitize
Return the indices of the bins to which each value in input tensor belongs.
mars.tensor.stats.chisquare
Calculate a one-way chi-square test.
mars.tensor.stats.power_divergence
Cressie-Read power divergence statistic and goodness of fit test.
mars.tensor.stats.ttest_1samp
Calculate the T-test for the mean of ONE group of scores.
mars.tensor.stats.ttest_ind
Calculate the T-test for the means of two independent samples of scores.
mars.tensor.stats.ttest_ind_from_stats
T-test for means of two independent samples from descriptive statistics.
mars.tensor.stats.ttest_rel
Calculate the t-test on TWO RELATED samples of scores, a and b.