Weather conditions influence the health of humans. Changing weather patterns may also cause considerable increase or decrease in the number of deaths. In this paper, we use daily data for Prague, Czech Republic, and the maximum overlap discrete wavelet transform to explore the time scale...

By modifying and generalizing the wavelet-based approach of approximately simulating univariate long-memory processes that is available in the literature, we propose a methodology for simulating a bivariate stationary process, whose components exhibit different relationships at different scales....

An interesting approach to economic and financial time series forecasting consists of decomposing an input time series additively into several components, each component capturing the dynamics of a different frequency range. Consequently, each component is modelled and forecasted separately, the...

Percival and Walden (2002) present a wavelet methodology of the least squares estimation of the long memory parameter for fractionally differenced processes. We suggest that the general idea of using wavelets for estimating long memory could be used for the estimation of long memory in time...

In this paper we explore the relative importance of the outside temperature and sunshine duration for the explanation of variations of electricity consumption in Prague, Czech Republic. An assessment of relative importance is made on various time scales ranging from the shortest ones associated...