Identification is the most important stage of all stages modeling process. This research identifies a suitable order for two different time series models ARIMA and GARCH. For GARCH distributions that GARCH-STD GARCH-GED with sample sizes in fitting forecasting stationary non-stationary data structures was considered. The study recommends use smallest information criterion like AIC BIC to select...

Spectral analysis considers the problem of determining (the art of recovering) the spectral content (i.e., the distribution of power over frequency) of a stationary time series from a finite set of measurements, by means of either nonparametric or parametric techniques. This paper introduces the spectral analysis problem, motivates the definition of power spectral density functions, and reviews...

We study consequences of stationary and semi-stationary set reflection. We show that the semi-stationary reflection principle implies the Singular Cardinal Hypothesis, the failure of weak square principle, etc. We also consider two cardinal tree properties introduced recently by Weiss and prove that they follow from stationary and semi-stationary set reflection augmented with a weak form of Mar...

In analyzing a signal, especially a non-stationary signal, it is often necessary the desired signal to be segmented into small epochs. Segmentation can be performed by splitting the signal at time instances where signal amplitude or frequency change. In this paper, the signal is initially decomposed into signals with different frequency bands using wavelet transform. Then, fractal dimension of ...

abstract in this paper, income per capita convergence hypothesis is tested in selected oic countries. for this purpose, we use the time series model and univariate kpss stationary test with multiple structural breaks (carrion-i-silvestre et al. (2005)) over the period 1950-2008. the results show that most oic countries could not catch up toward usa. although because of some positive term of tra...