Multiple outlier detection tests for parametric models

We propose a simple multiple outlier identification method for parametric location-scale and shape-scale models when the number of possible outliers is not specified. The method is based on a result giving asymptotic properties of extreme z-scores. Robust estimators of model parameters are used defining z-scores. An extensive simulation study was done for comparing of the proposed method with existing methods. For the normal family, the method is compared with the well known Davies-Gather, Rosner's, Hawking's and Bolshev's multiple outlier identification methods. The choice of an upper limit for the number of possible outliers in case of Rosner's test application is discussed. For other families, the proposed method is compared with a method generalizing Gather-Davies method. In most situations, the new method has the highest outlier identification power in terms of masking and swamping values. We also created R package outliersTests for proposed test

Statistical analysis of the generalized additive semiparametric survival model with random covariate

Generalizations of the additive hazards model are considered. Estimates of the regression parameters and baseline function are proposed, when covariates are random. The asymptotic properties of estimators are considered

Bolshev's method of confidence limit construction

Confidence intervals and regions for the parameters of a distribution are constructed, following the method due to L. N. Bolshev. This construction method is illustrated with Poisson, exponential, Bernouilli, geometric, normal and other distributions depending on parameters

Non-parametric tests for censored data/ Bagdonavicius

xviii, 233 hal.: tab.; 24 cm

Non-parametric tests for censored data/ Bagdonavicius

xviii, 233 hal.: tab.; 24 cm

Statistical analysis of survival and reliability data with multiple crossing of survival functions

The so-called MCE model with possible multiple crossing of survival functions is studied. Under this model the ratios of the hazard rates increase, decrease or are constant, the hazard rates and the survival functions do not intersect, intersect once or twice

On goodness-of-fit for homogeneity and proportional hazards, by V.Bagdonavicius and M.Nikulin

The classical goodness-of-fit tests for homogeneity and proportional hazards have small power in the case of alternatives when crossings of survival functions are possible. We give test statistics which are oriented against wide classes of alternatives including possible crossings of survival functions. The limit distributions of the test statistics are derived

Estimation of reliability using failure-degradation data with explanatiry variable.

Semiparametric estimation od degradation and failure process characteristics using degradation and multi-mode failure data with covariates is considered supposing that the component of hazard rate related with observable degradation is unknown function of degradation and may depend on covariates

Accelerated Life Testing

The properties of important class of reliability models are considered

Aging and degradation models in reliability and safety

The models describing dependance of thelifetime distribution on the time-depending explanatory variables are considered. Such models are useful in reliability and survival analysis to study the reliability of bio-medical systems