ﻻ يوجد ملخص باللغة العربية
Statistical parameters are used in finance, weather, industrial, science, among other vast number of different fields to draw conclusions. New more efficient selection methods are mandatory to analyses the huge amount of astronomical data. The standard and new data-mining parameters to analyses non-correlated data are used to set the best way to discriminate stochastic and non-stochastic variations. We introduce 16 modified statistical parameters covering different features of statistical distribution, like; average, dispersion, and shape parameters. Many of dispersion and shape parameters are unbound parameters, i.e. equations which do not require the calculation of the average. Moreover, the majority of them have lower error than previous ones that is mainly observed for distributions having few measurements. A set of non-correlated variability indices, sample size corrections, and a new noise model as well as tests of different apertures and cutoffs on the data (BAS approach) are introduced. The number of misselections is reduced by about 520% using a single waveband and 1200% combining all wavebands. On the other hand, the even mean also improves the correlated indices introduced in Paper 1 Ferreira Lopes & Cross (2016). The misselection rate is reduced by about 18% if the even mean is used instead of the mean to compute the correlated indices in the WFCAM database. Even statistics allows us to improve the effectiveness of both correlated and non-correlated indices. The correlated variability indices, proposed in the first paper of this series, are also improved if the even mean is used. The even parameters will also be useful for classifying light curves in the last step of this project. We consider that the first step of this project, where we set new techniques and methods that provide a huge improve on the efficiency of selection of variable stars, is now complete.
We survey our understanding of classical novae: non-terminal, thermonuclear eruptions on the surfaces of white dwarfs in binary systems. The recent and unexpected discovery of GeV gamma-rays from Galactic novae has highlighted the complexity of novae
In this paper, we present the FATS (Feature Analysis for Time Series) library. FATS is a Python library which facilitates and standardizes feature extraction for time series data. In particular, we focus on one application: feature extraction for ast
The changes of the spin depolarization length in zinc-blende semiconductors when an external component of correlated noise is added to a static driving electric field are analyzed for different values of field strength, noise amplitude and correlatio
The controversy over whether ultraluminous X-ray sources (ULXs) contain a new intermediate-mass class of black holes (IMBHs) remains unresolved. We present new analyses of the deepest XMM-Newton observations of ULXs that address their underlying natu
We present the results of a study aimed at exploring the evolution towards energy equipartition in star cluster models with different initial degrees of anisotropy in the velocity distribution. Our study reveals a number of novel aspects of the clust