Add to ORKGIn this paper a procedure for testing additivity in nonlinear time series analysis is provided. The method is based on: Generalized Likelihood Ratio Test(Zhang, 2001), Volterra expansion (Chen et al., 1995), and nonparametric conditional bootstrap (Jianqing and Qiwei, 2003). Investigations about performance (in terms of empirical size and power), and comparisons with other additivity tests proposed by Chen et al. (1995), are made recurring to Monte Carlo simulations
AbstractWe first establish the consistency of regressogram type estimators of the functions T and U ...
This paper proposes a test for selecting explanatory variables in nonparametric regression. The test...
Several diagnostic tests for the lack of fit time series models have been introduced using parametri...
Semiparametric generalized additive models are a powerful tool in quantitative econometrics. The mai...
Abstract This paper concerns statistical tests for simple structures such as parametric models, lowe...
This paper concerns statistical tests for simple structures such as parametric models, lower order m...
Various nonparametric kernel regression estimators are presented, based on which we consider two non...
In this paper we propose a new procedure for detecting additive outliers in a univariate time series...
We consider three nonparametric tests for functional form, varying parameters, and omitted variables...
In this article we propose a new test for additivity in nonparametric quantile regression with a hig...
An information theoretic test for Granger causality for stationary weakly dependent time series is p...
© Institute of Mathematical Statistics, 2009This paper considers a class of nonparametric autoregres...
In this paper, we consider testing for additivity in a class of nonparametric stochastic regression ...
The thesis concentrates on property of linearity in time series models, its definitions and possibil...
<p>The study of the effect of a treatment may involve the evaluation of a variable at a number of mo...
AbstractWe first establish the consistency of regressogram type estimators of the functions T and U ...
This paper proposes a test for selecting explanatory variables in nonparametric regression. The test...
Several diagnostic tests for the lack of fit time series models have been introduced using parametri...
Semiparametric generalized additive models are a powerful tool in quantitative econometrics. The mai...
Abstract This paper concerns statistical tests for simple structures such as parametric models, lowe...
This paper concerns statistical tests for simple structures such as parametric models, lower order m...
Various nonparametric kernel regression estimators are presented, based on which we consider two non...
In this paper we propose a new procedure for detecting additive outliers in a univariate time series...
We consider three nonparametric tests for functional form, varying parameters, and omitted variables...
In this article we propose a new test for additivity in nonparametric quantile regression with a hig...
An information theoretic test for Granger causality for stationary weakly dependent time series is p...
© Institute of Mathematical Statistics, 2009This paper considers a class of nonparametric autoregres...
In this paper, we consider testing for additivity in a class of nonparametric stochastic regression ...
The thesis concentrates on property of linearity in time series models, its definitions and possibil...
<p>The study of the effect of a treatment may involve the evaluation of a variable at a number of mo...
AbstractWe first establish the consistency of regressogram type estimators of the functions T and U ...
This paper proposes a test for selecting explanatory variables in nonparametric regression. The test...
Several diagnostic tests for the lack of fit time series models have been introduced using parametri...