Displaying similar documents to “Selective F tests for sub-normal models”

F and selective F tests with balanced cross-nesting and associated models

Célia Nunes, Iola Pinto, João Tiago Mexia (2006)

Discussiones Mathematicae Probability and Statistics

Similarity:

F tests and selective F tests for fixed effects part of balanced models with cross-nesting are derived. The effects of perturbations in the numerator and denominator of the F statistics are considered.

F-tests for generalized linear hypotheses in subnormal models

Joao Tiago Mexia, Gerberto Carvalho Dias (2001)

Discussiones Mathematicae Probability and Statistics

Similarity:

When the measurement errors may be assumed to be normal and independent from what is measured a subnormal model may be used. We define a linear and generalized linear hypotheses for these models, and derive F-tests for them. These tests are shown to be UMP for linear hypotheses as well as strictly unbiased and strongly consistent for these hypotheses. It is also shown that the F-tests are invariant for regular transformations, possess structural stability and are almost strongly consistent...

On a robust significance test for the Cox regression model

Tadeusz Bednarski, Filip Borowicz (2006)

Discussiones Mathematicae Probability and Statistics

Similarity:

A robust significance testing method for the Cox regression model, based on a modified Wald test statistic, is discussed. Using Monte Carlo experiments the asymptotic behavior of the modified robust versions of the Wald statistic is compared with the standard significance test for the Cox model based on the log likelihood ratio test statistic.

On testing variance components in unbalanced mixed linear model

Lýdia Širková, Viktor Witkovský (2001)

Applications of Mathematics

Similarity:

The paper presents some approximate and exact tests for testing variance components in general unbalanced mixed linear model. It extends the results presented by Seifert (1992) with emphasis on the computational aspects of the problem.

Unit root test under innovation outlier contamination small sample case

Lynda Atil, Hocine Fellag, Karima Nouali (2006)

Discussiones Mathematicae Probability and Statistics

Similarity:

The two sided unit root test of a first-order autoregressive model in the presence of an innovation outlier is considered. In this paper, we present three tests; two are usual and one is new. We give formulas computing the size and the power of the three tests when an innovation outlier (IO) occurs at a specified time, say k. Using a comparative study, we show that the new statistic performs better under contamination. A Small sample case is considered only.

Some remarks on permutation type tests in linear models

Marie Husková, Jan Picek (2004)

Discussiones Mathematicae Probability and Statistics

Similarity:

The paper discusses applications of permutation arguments in testing problems in linear models. Particular attention will be paid to the application in L₁-test procedures. Theoretical results will beaccompanied by a simulation study.

Aligned rank tests in measurement error model

Radim Navrátil, A. K. Md. Ehsanes Saleh (2016)

Applications of Mathematics

Similarity:

Aligned rank tests are introduced in the linear regression model with possible measurement errors. Unknown nuisance parameters are estimated first and then classical rank tests are applied on the residuals. Two situations are discussed: testing about an intercept in the linear regression model considering the slope parameter as nuisance and testing of parallelism of several regression lines, i.e. whether the slope parameters of all lines are equal. Theoretical results are derived and...

Generalized F tests and selective generalized F tests for orthogonal and associated mixed models

Célia Nunes, Iola Pinto, João Tiago Mexia (2008)

Discussiones Mathematicae Probability and Statistics

Similarity:

The statistics of generalized F tests are quotients of linear combinations of independent chi-squares. Given a parameter, θ, for which we have a quadratic unbiased estimator, θ̃, the test statistic, for the hypothesis of nullity of that parameter, is the quotient of the positive part by the negative part of such estimator. Using generalized polar coordinates it is possible to obtain selective generalized F tests which are especially powerful for selected families of alternatives. We...

The and the Peas: An Intuitive Modeling Approach to Hypothesis Testing

C. Neuhauser, E. Stanley (2011)

Mathematical Modelling of Natural Phenomena

Similarity:

We propose a novel approach to introducing hypothesis testing into the biology curriculum. Instead of telling students the hypothesis and what kind of data to collect followed by a rigid recipe of testing the hypothesis with a given test statistic, we ask students to develop a hypothesis and a mathematical model that describes the null hypothesis. Simulation of the model under the null hypothesis allows students to compare their experimental...

Testing Linearity in an AR Errors-in-variables Model with Application to Stochastic Volatility

D. Feldmann, W. Härdle, C. Hafner, M. Hoffmann, O. Lepski, A. Tsybakov (2003)

Applicationes Mathematicae

Similarity:

Stochastic Volatility (SV) models are widely used in financial applications. To decide whether standard parametric restrictions are justified for a given data set, a statistical test is required. In this paper, we develop such a test of a linear hypothesis versus a general composite nonparametric alternative using the state space representation of the SV model as an errors-in-variables AR(1) model. The power of the test is analyzed. We provide a simulation study and apply the test to...