Optimal accelerated degradation test (ADT) plans are developed assuming that the constant-stress loading method is employed and the degradation characteristic follows a Wiener process. Unlike the previous works on planning ADTs based on stochastic process models, this article determines the test...

The purpose of this paper is to propose a time-varying vector autoregressive model (TV-VAR) for forecasting multivariate time series. The model is casted into a state-space form that allows flexible description and analysis. The volatility covariance matrix of the time series is modelled via...

In this paper, we propose a new nonparametric simultaneous test for dual alternatives. Simultaneous tests for dual alternatives are used for pattern detection of <italic>arsenic contamination</italic> level in ground water. We consider two possible patterns, namely, monotone shift and an umbrella-type location...

Vangeneugden <italic>et al.</italic> [15] derived approximate correlation functions for longitudinal sequences of general data type, Gaussian and non-Gaussian, based on generalized linear mixed-effects models (GLMM). Their focus was on binary sequences, as well as on a combination of binary and Gaussian...

Processes of serially dependent Poisson counts are commonly observed in real-world applications and can often be modeled by the first-order integer-valued autoregressive (INAR) model. For detecting positive shifts in the mean of a Poisson INAR(1) process, we propose the one-sided s exponentially...

For the univariate case, the <italic>R</italic> chart and the <italic>S</italic> -super-2 chart are the most common charts used for monitoring the process dispersion. With the usual sample size of 4 and 5, the <italic>R</italic> chart is slightly inferior to the <italic>S</italic> -super-2 chart in terms of efficiency in detecting process shifts. In this...

The Zero-inflated Poisson distribution has been used in the modeling of count data in different contexts. This model tends to be influenced by outliers because of the excessive occurrence of zeroes, thus outlier identification and robust parameter estimation are important for such distribution....

The robust estimation and the local influence analysis for linear regression models with scale mixtures of multivariate skew-normal distributions have been developed in this article. The main virtue of considering the linear regression model under the class of scale mixtures of skew-normal...