In several testing problems we have big datasets. For instance, we could have a large number of response variables. Parametric methods, such as Hotelling T-square test, cannot be applied when the number of outcomes is greater than the sample sizes. Furthermore, strong assumptions such as homoskedasticity and normality are not plausible. We focus on two-sample multivariate problems and propose a nonparametric solution based on a permutation test.
Nonparametric Method for MUltivariate Tests with Big Data
Stefano BonniniCo-primo
2021
Abstract
In several testing problems we have big datasets. For instance, we could have a large number of response variables. Parametric methods, such as Hotelling T-square test, cannot be applied when the number of outcomes is greater than the sample sizes. Furthermore, strong assumptions such as homoskedasticity and normality are not plausible. We focus on two-sample multivariate problems and propose a nonparametric solution based on a permutation test.File in questo prodotto:
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