The results of a Monte Carlo study of the size and power of parametric and semiparametric approaches to inference on covariate effects in survival (time-to-events) models in the presence of model misspecification and an independent censoring mechanism are reported. Basic models employed are a parametric model, where both a baseline distribution and the dependence structure of covariates on the ...

Abrupt shifts in the level of a time series represent important information and should be preserved in statistical signal extraction. We investigate rules for detecting level shifts that are resistant to outliers and which work with only a short time delay. The properties of robustified versions of the t-test for two independent samples and its non-parametric alternatives are elaborated under d...

This paper provided an insight to the effective use of inferential statistics for social and behavioural research. As a theoretical paper, it explored the importance of tests of significance emphasizing the need to use the appropriate test for a particular research. It showed that a parametric test is one that involves the estimation of the value of at list one population parameter and the fact...

Rescaling of nominaland ordinal-scaled data to interval-scaled data is an important preparatory step prior to applying parametric statistical tests. Without rescaling, the analyst typically must resort to non-parametric tests that are less robust statistically than the metric counterparts. Multi-dimensional scaling (MDS) is a procedure that can be used to perform the desired rescaling. This pap...

The traffic within the branches of a communication network is often a random variable with an approximate multivariate normal distribution. The analysis of such systems has been discussed in a previous paper. In this paper, we consider the optimum synthesis problem. Nonlinear and linear programming is used to guarantee that a given flow rate probability between a specified pair of terminals is ...

Introduction and Motivation: fMRI is a natural source of high-dimensional time series data. Recordings are typically acquired in several hour sessions, with processing and analysis done offline. Due to the short amount of recording time available from any session, there is an imbalance between the comparatively small number of time slices and the high dimensionality of the data at each slice. A...