Add to ORKGThe subject of the thesis is the autocorrelation structure of time series. AR(1) process is studied as a special example. An estimator of the variance of the sample autocorre- lation is derived and its asymptotic properties are proved. We investigate the convergence of the variance estimates of sample autocorrelations in some simulated series. Further, the empirical significance level and power of selected autocorrelation tests are calculated.
1-1. In the analysis of. most time series it is customary to estimate the mean and the trend by fitt...
Abstract. A method is proposed for estimating, in a consistent way, the asymptotic covariance struct...
When the elements of a stationary ergodic time series have finite variance the sample correlation fu...
Práce se zabývá autokorelační strukturou časových řad, konkrétně i procesu AR(1). Je odvozen odhad r...
In the first part of the study, nine estimators of the first-order autoregressive parameter are revi...
A random coefficient autoregressive process is deeply investigated in which the coefficients are cor...
International audienceWe are interested in the implications of a linearly autocorrelated driven nois...
Testing the presence of serial correlation in the error terms in fixed effects regression models is ...
Time series generated by Stochastic Volatility (SV) processes are uncorrelated although not independ...
Serial correlation can seriously affect the performance of traditional control charts. Many authors ...
Abstract. This paper analyses the asymptotic behaviour of the autocorrelation structure exhibited by...
The authors show how Kendall's tau can be adapted to test against serial dependence in a univariate ...
In the classical linear regression model we assume that successive values of the disturbance term ar...
The sample autocorrelation function is defined by the mean lagged products (LPs) of random observati...
Since sample autocorrelations play a key role in identification of time series models, the study of ...
1-1. In the analysis of. most time series it is customary to estimate the mean and the trend by fitt...
Abstract. A method is proposed for estimating, in a consistent way, the asymptotic covariance struct...
When the elements of a stationary ergodic time series have finite variance the sample correlation fu...
Práce se zabývá autokorelační strukturou časových řad, konkrétně i procesu AR(1). Je odvozen odhad r...
In the first part of the study, nine estimators of the first-order autoregressive parameter are revi...
A random coefficient autoregressive process is deeply investigated in which the coefficients are cor...
International audienceWe are interested in the implications of a linearly autocorrelated driven nois...
Testing the presence of serial correlation in the error terms in fixed effects regression models is ...
Time series generated by Stochastic Volatility (SV) processes are uncorrelated although not independ...
Serial correlation can seriously affect the performance of traditional control charts. Many authors ...
Abstract. This paper analyses the asymptotic behaviour of the autocorrelation structure exhibited by...
The authors show how Kendall's tau can be adapted to test against serial dependence in a univariate ...
In the classical linear regression model we assume that successive values of the disturbance term ar...
The sample autocorrelation function is defined by the mean lagged products (LPs) of random observati...
Since sample autocorrelations play a key role in identification of time series models, the study of ...
1-1. In the analysis of. most time series it is customary to estimate the mean and the trend by fitt...
Abstract. A method is proposed for estimating, in a consistent way, the asymptotic covariance struct...
When the elements of a stationary ergodic time series have finite variance the sample correlation fu...