Add to ORKGThe book addressed the testing of hypotheses in non-parametric models in the general case for complete data samples. Classical non-parametric tests (goodness-of-fit , homogenneity, randomness, independence) of complete data are considered and explained. Tests features include the chi-squared and modified chi-squared tests, rank and homogeneity tests, and most of the test results are proved, with real applicatiuons illustrated using examples. The incorrect use of many tests, and their applications using commonly deployed statistical software is highlighted and discuss
Tests for parametric nonhomogeneous and homogeneous Markov processes are given. Asymptotic distribut...
Suppose a smooth test of goodness of fit has been applied to assess the validity of a parametric ana...
In general, statistical methods have two categories: parametric and nonparametric. Parametric analys...
The book addressed the testing of hypotheses in non-parametric models in the general case for comple...
This book addresses the testing of hypothses in non-parametric models in the specific case of censor...
A parametric test specifies certain conditions about the distribution of responses in the populatio...
Although non-parametric tests have already been proposed for that pur-pose, statistical significance...
Although non-parametric tests have already been proposed for that pur-pose, statistical significance...
The testing of statistical hypotheses concerning two populations consists in determining the relatio...
This textbook provides a self-contained presentation of the main concepts and methods of nonparametr...
Most statistical methods require assumptions about the populations from which samples are taken. Usu...
Several new tests are proposed for examining the adequacy of a family of parametric models against l...
The nonparametric methods are most suitable for tasks facing the uncertainty or complexity of models...
Mixed models, with both random and fixed effects, are most often estimated on the assump-tion that t...
General methods for testing the fit of a parametric function are proposed. The idea underlying each ...
Tests for parametric nonhomogeneous and homogeneous Markov processes are given. Asymptotic distribut...
Suppose a smooth test of goodness of fit has been applied to assess the validity of a parametric ana...
In general, statistical methods have two categories: parametric and nonparametric. Parametric analys...
The book addressed the testing of hypotheses in non-parametric models in the general case for comple...
This book addresses the testing of hypothses in non-parametric models in the specific case of censor...
A parametric test specifies certain conditions about the distribution of responses in the populatio...
Although non-parametric tests have already been proposed for that pur-pose, statistical significance...
Although non-parametric tests have already been proposed for that pur-pose, statistical significance...
The testing of statistical hypotheses concerning two populations consists in determining the relatio...
This textbook provides a self-contained presentation of the main concepts and methods of nonparametr...
Most statistical methods require assumptions about the populations from which samples are taken. Usu...
Several new tests are proposed for examining the adequacy of a family of parametric models against l...
The nonparametric methods are most suitable for tasks facing the uncertainty or complexity of models...
Mixed models, with both random and fixed effects, are most often estimated on the assump-tion that t...
General methods for testing the fit of a parametric function are proposed. The idea underlying each ...
Tests for parametric nonhomogeneous and homogeneous Markov processes are given. Asymptotic distribut...
Suppose a smooth test of goodness of fit has been applied to assess the validity of a parametric ana...
In general, statistical methods have two categories: parametric and nonparametric. Parametric analys...