The empirical process of the residuals from general autoregressions is investigated. If an intercept is included in the regression, the empirical process is asymptotically Gaussian and free of nuisance parameters. This contrasts the known result that in the unit root case without intercept the...

In this paper, we propose a model-free bootstrap method for the empirical process under absolute regularity. More precisely, consistency of an adapted version of the so-called dependent wild bootstrap, that was introduced by Shao (2010) and is very easy to implement, is proved under minimal...

We present some methods for the estimation and testing of usual ergodic interest rate models based on the observation of the short interest rate on the monetary market. First, we develop a test of type Kolmogorov-Smirnov for ergodic diffusion processes. We extend the results to the case where...

In this paper, we propose a model-free bootstrap method for the empirical process under absolute regularity. More precisely, consistency of an adapted version of the so-called dependent wild bootstrap, that was introduced by Shao (2010) and is very easy to implement, is proved under minimal...

In this paper, we propose a model-free bootstrap method for the empirical process under absolute regularity. More precisely, consistency of an adapted version of the so-called dependent wild bootstrap, that was introduced by Shao (2010) and is very easy to implement, is proved under minimal...

We propose new affine invariant tests for multivariate normality, based on independence characterizations of the sample moments of the normal distribution. The test statistics are obtained using canonical correlations between sets of sample moments in a way that resembles the construction of...

The Shapiro–Wilk test (SW) and the Anderson–Darling test (AD) turned out to be strong procedures for testing for normality. They are joined by a class of tests for normality proposed by Epps and Pulley that, in contrast to SW and AD, have been extended by Baringhaus and Henze to yield...

Monte Carlo methods are used to study the size and the power of three versions of the Jarque and Bera LM test for normality, JB( 1 2 g , g ), JB( 1 2 b ,b ), and finally JB( 1 2 k ,k ). The difference between these tests comes from the different definitions (estimates) of sample skewness and...

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...