statsmodels.stats.robust_compare.TrimmedMean

class statsmodels.stats.robust_compare.TrimmedMean(data, fraction, is_sorted=False, axis=0)[source]

class for trimmed and winsorized one sample statistics

axis is None, i.e. ravelling, is not supported

Attributes
data_trimmed
data_winsorized

winsorized data

mean_trimmed

mean of trimmed data

mean_winsorized

mean of winsorized data

std_mean_trimmed

standard error of trimmed mean

std_mean_winsorized

standard error of winsorized mean

var_winsorized

variance of winsorized data

Methods

reset_fraction(frac)

create a TrimmedMean instance with a new trimming fraction

ttest_mean([value, transform, alternative])

One sample ttest for trimmed or Winsorized mean

Properties

data_trimmed

data_winsorized

winsorized data

mean_trimmed

mean of trimmed data

mean_winsorized

mean of winsorized data

std_mean_trimmed

standard error of trimmed mean

std_mean_winsorized

standard error of winsorized mean

var_winsorized

variance of winsorized data