Bootstrapping the Seasonal Means and the Overall Mean in Rainfall Time Series

Abstract

Several bootstrap methods have been studied nowadays for estimating the parameters in periodic data and it is important to consider the periodicity present in choosing the right bootstrap method. In this study we conducted a comparison of the performance of several block bootstrap methods designed for dependent data in the case of a real data time series with periodic structure such as the rainfall time series that is a time series with meteorological data collected monthly in a region in Albania. R programming language is used to perform the bootstrap and to obtain the results. We proposed a block bootstrap procedure in the case of estimating the seasonal means and the overall mean in the time series studied and based on the results obtained we notice a good performance of our proposed bootstrap procedure compared with other procedures considered.

Received: 12 January 2023 / Accepted: 16 March 2023 / Published: 20 March 2023