This paper presents nonparametric tests of independence that can be used to test the independence of p random variables, serial independence for time series, or residuals data. These tests are shown to generalize the classical portmanteau statistics. Applications to both time series and regression r
Towards a nonparametric test of linearity for times series
β Scribed by Ricardo Rios
- Publisher
- Elsevier Science
- Year
- 1998
- Tongue
- English
- Weight
- 906 KB
- Volume
- 68
- Category
- Article
- ISSN
- 0378-3758
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β¦ Synopsis
We study the intervals of linearity for the regression function of stationary and strongly mixing vectorial-valued random processes, using nonlinear integral plug-in estimators of functionals of the second derivative of the regression function. We give conditions in order to obtain CLT, possibly degenerated, for these estimators at the semiparametric rate v ~. Simulations for a test statistic based on these estimators under linearity and nonlinearity conditions are given.
π SIMILAR VOLUMES
In a recent paper Azzalini and Bowman (1993, J. Roy. Statist. Soc. Ser. B 55, 549 -559) proposed a pseudolikelihood ratio test for checking the linearity in a homoscedastic nonparametric regression model under a ΓΏxed design assumption. In this paper, we study the asymptotic properties of this test a
## Abstract The problem of prediction in time series using nonparametric functional techniques is considered. An extension of the local linear method to regression with functional explanatory variable is proposed. This forecasting method is compared with the functional NadarayaβWatson method and wi
We have developed a new test for non-linearity in time series data in discrete time. A comparative study has been conducted on Subba Rao, Gabr and Hinich's test, Keenan's test, Petruccelli and Davies' test, and the new test. Both simulated and real data are used in the study. The implication for for
We propose tests for Gaussianity of a vector stationary time series based on multivariate measures of skewness and kurtosis. The tests are illustrated by two real sets of data. We discuss briefly some properties of linear transforms of vector time series, and stress the need for separate tests for l