An empirical likelihood goodness-of-fit test for time series
نویسندگان
چکیده
منابع مشابه
An empirical likelihood goodness-of-fit test for time series
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...
متن کاملA Conditional Goodness-of-Fit Test for Time Series
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...
متن کاملAn Empirical Likelihood Approach To Goodness of Fit Testing
Motivated by applications to goodness of fit testing, the empirical likelihood approach is generalized to allow for the number of constraints to grow with the sample size and for the constraints to use estimated criteria functions. The latter is needed to handle naturally occurring nuisance parameters. A central limit theorem is proved to deal with quadratic forms based on random vectors of inc...
متن کاملAn empirical goodness-of-fit test for multivariate distributions
An empirical test is presented by which one may determine whether a specified multivariate probability model is suitable to describe the underlying distribution of a set of observations. This test is based on the premise that, given any probability distribution, the Mahalanobis distances corresponding to data generated from that distribution will likewise follow a distinct distribution that can...
متن کاملAn empirical likelihood ratio based goodness-of-fit test for Inverse Gaussian distributions
The Inverse Gaussian (IG) distribution is commonly introduced to model and examine right skewed data having positive support. When applying the IG model, it is critical to develop efficient goodness-of-fit tests. In this article, we propose a new test statistic for examining the IG goodness-of-fit based on approximating parametric likelihood ratios. The parametric likelihood ratio methodology i...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of the Royal Statistical Society: Series B (Statistical Methodology)
سال: 2003
ISSN: 1369-7412
DOI: 10.1111/1467-9868.00408