Abstract. 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 hypotheses, we prove that the power converges to one. The performance of our test procedure is illustrated from different simulated series. In particular, we compare its size and its power with test of Chen and Deo. Mathematics Subject Classification. 60F05, 62F03. 1. Introduction an
A frequency-domain statistic is introduced to test for stationarity versus stochastic or determinist...
This study considers the goodness of fit test for a class of conditionally heteroscedastic location-...
This paper studies a class of tests useful for testing goodness of fit of a wide variety of time ser...
In a recent paper Fay and Philippe (2002) proposed a goodness-of-fit test for long-range dependent p...
This article proposes a class of goodness-of-fit tests for the autocorrela-tion function of a time s...
This article proposes a class of goodness-of-fit tests for the autocorrelation function of a time se...
Abstract: In this paper we study the asymptotic behaviour of empirical processes when parameters are...
A new frequency-domain test statistic is introduced to test for short memory versus long memory. We ...
The length of the graph of an estimate of the distribution function is used as a measure of goodness...
This paper proposes a model specification testing procedure for parametric specification of the cond...
This paper proposes a model specification testing procedure for parametric specification of the cond...
The goodness-of-fit tests for time series models have been discussed for years. Most of the current ...
We present a goodness of fit test for time series models based on the discrete spectral average esti...
AbstractWe derive a functional central limit theorem for the empirical spectral measure or discretel...
An important problem in time series analysis is the discrimination between non-stationarity and long...
A frequency-domain statistic is introduced to test for stationarity versus stochastic or determinist...
This study considers the goodness of fit test for a class of conditionally heteroscedastic location-...
This paper studies a class of tests useful for testing goodness of fit of a wide variety of time ser...
In a recent paper Fay and Philippe (2002) proposed a goodness-of-fit test for long-range dependent p...
This article proposes a class of goodness-of-fit tests for the autocorrela-tion function of a time s...
This article proposes a class of goodness-of-fit tests for the autocorrelation function of a time se...
Abstract: In this paper we study the asymptotic behaviour of empirical processes when parameters are...
A new frequency-domain test statistic is introduced to test for short memory versus long memory. We ...
The length of the graph of an estimate of the distribution function is used as a measure of goodness...
This paper proposes a model specification testing procedure for parametric specification of the cond...
This paper proposes a model specification testing procedure for parametric specification of the cond...
The goodness-of-fit tests for time series models have been discussed for years. Most of the current ...
We present a goodness of fit test for time series models based on the discrete spectral average esti...
AbstractWe derive a functional central limit theorem for the empirical spectral measure or discretel...
An important problem in time series analysis is the discrimination between non-stationarity and long...
A frequency-domain statistic is introduced to test for stationarity versus stochastic or determinist...
This study considers the goodness of fit test for a class of conditionally heteroscedastic location-...
This paper studies a class of tests useful for testing goodness of fit of a wide variety of time ser...