Nonparametric Tests for Multi-Sample Problems¶
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multisample.
hettmansperger_norton_test
(data, group, alternative='increasing', trend=None)[source]¶ Function to calculate the Hettmansperger-Norton test.
- Args:
data (list(float)): data from all groups
group (list(int)): group factor
alternative (str): either ‘increasing’, ‘decreasing’ or ‘custom’
trend (list(float)): a vector specifying the alternative; only used, if alternative = ‘custom’
- Returns:
namedtuple(‘HettmanspergerNortonResult’, (‘alternative’, ‘weight’, ‘statistic’, ‘pvalue’)):
chosen alternative (str)
trend (list(float))
test statistic (float)
one sided p-value (float)
- References:
- Hettmansperger, T. P., & Norton, R. M. (1987). Tests for patterned alternatives in k-sample problems. Journal of the American Statistical Association, 82(397), 292-299.
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multisample.
kruskal_wallis_test
(data, group, pseudoranks=True)[source]¶ Function to calculate the Kruskal-Wallis test. It is recommended to use pseudo-ranks as ranks may lead to paradoxical results.
Null hypothesis H_0: F_1 = … F_a
- Args:
data (list(float)): data from all groups
group (list(int)): group factor
pseudoranks (bool): True if pseudo-ranks instead of ranks are used
- Returns:
namedtuple(‘KruskalWallisResult’, (‘statistic’, ‘pvalue’)):
test statistic (float)
p-value (float)