A Parametric Bootstrap Version of Hedges’ Homogeneity Test

A Parametric Bootstrap Version of Hedges’ Homogeneity Test

Parametric Bootstrap for Test of Contrast Difference in Neural Networks

This work concernes the contrast difference test and its asymptotic properties for non linear auto-regressive models. Our approach is based on an application of the parametric bootstrap method. It is a re-sampling method based on the estimate parameters of the models. The resulting methodology is illustrated by simulations of multilayer perceptron models, and an asymptotic justification is give...

Comparison of parametric and bootstrap method in bioequivalence test.

The estimation of 90% parametric confidence intervals (CIs) of mean AUC and Cmax ratios in bioequivalence (BE) tests are based upon the assumption that formulation effects in log-transformed data are normally distributed. To compare the parametric CIs with those obtained from nonparametric methods we performed repeated estimation of bootstrap-resampled datasets. The AUC and Cmax values from 3 a...

Bootstrap Methods for Testing Homogeneity of Variances

This paper describes the use of bootstrap and permutation methods for lhe problem of testing homogeneity of variances when means are not assumed equal or known. The melhods are new in this context, and nontrivial, since lhe composite null hypothesis involves nuisance mean parameters. They allow the use of normal-:'theory test statistics such as F = sUs~ without the normality assumption which is...

A parametric representation of linguistic hedges in Zadeh's fuzzy logic

This paper proposes a model for the parametric representation of linguistic hedges in Zadeh’s fuzzy logic. In this model each linguistic truth-value, which is generated from a primary term of the linguistic truth variable, is identified by a real number r depending on the primary term. It is shown that the model yields a method of efficiently computing linguistic truth expressions accompanied w...