A Robust Test for Omnibus Alternatives

Robust Tests in Regression Models With Omnibus Alternatives and Bounded Influence

A robust approach for testing the parametric form of a regression function versus an omnibus alternative is introduced. This generalizes existing robust methods for testing subhypotheses in a regression model. The new test is motivated by developments in modern smoothingbased testing procedures and can be viewed as a robustification of a smoothing-based conditional moment test. It is asymptotic...

A Directional Test for Average Partial Effects in Linear Regression

For the OLS estimators in a classical linear model to have average partial effects interpretation, one usually imposes the so-called “strict exogeneity”condition. In practice, testing strict exogeneity condition can be done by omnibus nonparametric test. However, there are cases where strict exogeneity condition fails but the average partial effects interpretation of OLS estimator still survive...

Frequentist-Bayes Lack-of-Fit Tests Based on Laplace Approximations

The null hypothesis that all of a function’s Fourier coefficients are 0 is tested in frequentist fashion using as test statistic a Laplace approximation to the posterior probability of the null hypothesis. Testing whether or not a regression function has a prescribed linear form is one application of such a test. In contrast to BIC, the Laplace approximation depends on prior probabilities, and ...

Robust Critical Values for the Jarque-bera Test for Normality

We introduce the “sample” technique to generate robust critical values for the Jarque and Bera (JB) Lagrangian Multiplier (LM) test for normality, JBCV( 1 2 , k k ), by using improved critical values the true size of the test approaches its nominal value. Monte Carlo methods are used to study the size, and the power of the JB normality test with the “sample” critical values and compare with thr...

ANCOVA: A Robust Omnibus Test Based On Selected Design Points