In the paper several proposals for exact or at least conservative parametric multivariate tests in the general linear model are considered that are also applicable for high-dimensional data, where the dimension of the observations may exceed the sample size. The common feature is the inclusion of principal component transformations into the test. Whereas a test proposal by Srivastava and von Ro...

One of the implications of the creation of Basel Committee on Banking Supervision was the implementation of Value-at-Risk (VaR) as the standard tool for measuring market risk and of out-of-sample backtesting for banking risk monitoring. We stress in this article that the results derived from this exercise can be spurious if one does not carry out a previous in-sample specification test to deter...

Recently Chen and Fan (2003a) introduced a new class of semiparametric copula-based multivariate dynamic (SCOMDY) models. A SCOMDY model specifies the conditional mean and the conditional variance of a multivariate time series parametrically (such as VAR, GARCH), but specifies the multivariate distribution of the standardized innovation semiparametrically as a parametric copula evaluated at non...

survival analysis is a set of methods used for analysis of the data which exist until the occurrence of an event. this study aimed to compare the results of the use of the semi-parametric cox model with parametric models to determine the factors influencing the length of stay of patients in the inpatient units of women hospital in tehran, iran. in this historical cohort study all 3421 charts of...

BACKGROUND During the last 30 years, the median sample size of research studies published in high-impact medical journals has increased manyfold, while the use of non-parametric tests has increased at the expense of t-tests. This paper explores this paradoxical practice and illustrates its consequences. METHODS A simulation study is used to compare the rejection rates of the Wilcoxon-Mann-Whi...

We propose two new types of nonparametric tests for investigating multivariate regression functions. The tests are based on cumulative sums coupled with either minimum volume sets or inverse regression ideas; involving no multivariate nonparametric regression estimation. The methods proposed facilitate the investigation for different features such as if a multivariate regression function is (i)...

Strandberg and Iglewicz (2012) propose a test that detects deviations from randomness, without an a priori distributional assumption. This nonparametric test is designed to detect deviations of neighboring observations from randomness, especially when the dataset consists of time series observations. The proposed test is especially effective for larger datasets. In our simulation study, this te...

We present a Poisson process formulation for studying the association between environmental covariates and recurrent events. The standard methods, which compare the covariate values (at event times) of the individuals having the event with those of the individuals at risk at that time, cannot accommodate environmental covariates, because they are identical for all individuals at risk. We sugges...

Listening tests and Mean Opinion Scores (MOS) are the most commonly used techniques for the evaluation of speech synthesis quality and naturalness. These are invaluable in the assessment of subjective qualities of machine generated stimuli. However, there are a number of challenges in understanding the MOS scores that come out of listening tests. Primarily, we advocate for the use of non-parame...