This paper proposes a distribution-free multivariate statistical process control (MSPC) chart to detect general distributional changes in multivariate process variables. The chart is deployed based on a multivariate goodness-of-fit test, which is extensible to high dimensional observations. The chart also employs data-dependent control limits, which are computed on line along with the charting ...

In this paper, we propose a goodness of fit test for continuous time stochastic volatility models based on discretely sampled observations. The proposed test is constructed by measuring deviations between the empirical and true characteristic functions obtained from the hypothesized stochastic volatility model. In this study, both the test statistics based on the fixed and decreasing sampling s...

In this paper we propose a nonparametric test for conditional heteroskedasticity based on a new measure of nonparametric goodness-of-fit (R2). In analogy with the ANOVA tools for classical linear regression models, the nonparametric R2 is obtained for the local polynomial regression of the residuals from a parametric regression on some covariates. It is close to 0 under the null hypothesis of c...

The Hosmer-Lemeshow goodness of fit test is w ell known when data are obtained from a simple random survey. The procedure involves grouping of the observations based on the expected probabilities and then testing the hypothesis that the difference between observed and expected events is simultaneously zero for all the groups. We consider the weighted analog of the hypothesis and propose a test ...

In this paper, we make use of the information measure introduced by Mokkadem (1997) for building a goodness-of-fit test for long-range dependent processes. Our test statistic is performed in the frequency domain and writes as a non linear functional of the normalized periodogram. We establish the asymptotic distribution of our statistic under the null hypothesis. Under specific alternative hypo...

This paper proposes a uni ed approach for consistent testing of linear restrictions on the conditional distribution function of a time series. A wide variety of interesting hypotheses in economics and nance correspond to such restrictions, including hypotheses involving conditional goodness-oft, conditional homogeneity, conditional mixtures, conditional quantiles, conditional symmetry, distribu...

Goodness of fit test procedures for the zeta parametric family based on quadratic distances and the Box--Cox transform are developed. Test statistics based on quadratic distances are shown to follow a chi-square distribution asymptotically. Test procedures based on the Box-Cox transform make use of the estimator of the parameter introduced by the Box-Cox transform, and numerical computations ar...

Standard goodness-of-fit tests for a parametric regression model against a series of nonparametric alternatives are based on residuals arising from a fitted model.When a parametric regression model is compared with a nonparametric model, goodness-of-fit testing can be naturally approached by evaluating the likelihood of the parametric model within a nonparametric framework. We employ the empiri...

There are several theorical results about order statistics and copulas in the literature that have  been mentioned also by Nelsen cite{p20}. The present study after reviewing some of these results, relies on  simulation technique to investigate the mentioned results about order statistics and copulas. The study concentrates on two well known Archimedean Gumbel and Frank families in the case tha...