Simultaneous Inference on All Linear Combinations of Means with Heteroscedastic Errors

Simultaneous Inference on All Linear Combinations of Means with Heteroscedastic Errors

We proposed a statistical method to construct simultaneous confidence intervals on all linear combinations of means without assuming equal variance where the classical Scheffé’s simultaneous confidence intervals no longer preserve the familywise error rate FWER . The proposed method is useful when the number of comparisons on linear combinations of means is extremely large. The FWERs for propos...

Aligned rank tests for the linear model with heteroscedastic errors

We consider the problem of testing subhypotheses in a heteroscedastic linear regression model. The proposed test statistics are based on the ranks of scaled residuals obtained under the null hypothesis. Any estimator that is n”2-consistent under the null hypothesis can be used to form the residuals. The error variances are estimated through a parametric model. This extends the theory of aligned...

on the effect of linear & non-linear texts on students comprehension and recalling

چکیده ندارد.

Inference for linear models with dependent errors

The paper is concerned with inference for linear models with fixed regressors and weakly dependent stationary time series errors. Theoretically, we obtain asymptotic normality for the M -estimator of the regression parameter under mild conditions and establish a uniform Bahadur representation for recursive M -estimators. Methodologically, we extend the recently proposed self-normalized approach...

Modeling of Heteroscedastic Measurement Errors