منابع مشابه
Bootstrap Methods for Time Series
The chapter gives a review of the literature on bootstrap methods for time series data. It describes various possibilities on how the bootstrap method, initially introduced for independent random variables, can be extended to a wide range of dependent variables in discrete time, including parametric or nonparametric time series models, autoregressive and Markov processes, long range dependent t...
متن کاملBootstrap Methods for Time Series
The bootstrap is a method for estimating the distribution of an estimator or test statistic by resampling one’s data or a model estimated from the data. The methods that are available for implementing the bootstrap and the accuracy of bootstrap estimates depend on whether the data are a random sample from a distribution or a time series. This paper is concerned with the application of the boots...
متن کاملBootstrap Methods for Time Series
The bootstrap is a method for estimating the distribution of an estimator or test statistic by resampling one’s data or a model estimated from the data. The methods that are available for implementing the bootstrap and the accuracy of bootstrap estimates depend on whether the data are a random sample from a distribution or a time series. This paper is concerned with the application of the boots...
متن کاملSieve Bootstrap for Time Series Sieve Bootstrap for Time Series
We study a bootstrap method which is based on the method of sieves. A linear process is approximated by a sequence of autoregressive processes of order p = pn, where pn ! 1 ; p n = on as the sample size n ! 1. F or given data, we t h e n estimate such a n A R pn model and generate a bootstrap sample by resampling from the residuals. This sieve bootstrap enjoys a nice nonparametric property. We ...
متن کاملSemiparametric Bootstrap Prediction Intervals in time Series
One of the main goals of studying the time series is estimation of prediction interval based on an observed sample path of the process. In recent years, different semiparametric bootstrap methods have been proposed to find the prediction intervals without any assumption of error distribution. In semiparametric bootstrap methods, a linear process is approximated by an autoregressive process. The...
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ژورنال
عنوان ژورنال: International Statistical Review
سال: 2003
ISSN: 0306-7734,1751-5823
DOI: 10.1111/j.1751-5823.2003.tb00485.x