Most of time series that appear in many economical geophysical and other phenomena are driven by nonGaussian white noise ( ), in this paper investigate some probabilistic properties of Gaussian and nonGaussian mixed with identification methods of ARMA model. We have theoretically derived the characteristic function the first of (four moments) of skeweness and kurtosis coefficients for white noi...

This work demonstrates the attractivity of alpha-skew hyperbolic secant distribution, a new skewed distribution based on technique and distribution. In first part, we determine its main features, including cumulative function, modality, non-central moments, skewness, kurtosis, moment generating function characteristic function. The remaining part is devoted to model applicability in statistical...

The pair correlation function is a fundamental spatial point process characteristic that, given the intensity function, determines second order moments of the point process. Non-parametric estimation of the pair correlation function is a typical initial step of a statistical analysis of a spatial point pattern. Kernel estimators are popular but especially for clustered point patterns suffer fro...

Given a closed quantum system, the states that can be reached with cyclic process are those same spectrum as initial state. Here we prove that, under very general assumption on Hamiltonian, distribution of mean extractable work is close to gaussian respect Haar measure. We derive bounds for both moments energy state and its characteristic function, showing discrepancy normal increasingly suppre...

Thermodynamic quantities, like heat, entropy, or work, are random variables, in stochastic systems. Here, we investigate the statistics of heat exchanged by a Brownian particle subjected to logarithm-harmonic potential. We derive analytically characteristic function and its moments for heat. Through numerical integration, simulation, calculate probability distribution as well, characterizing fu...

Gait is a biometric feature and gait recognition has become a challenging problem in computer vision. New wavelet velocity moments have been developed to describe and recognize gait. Wavelet moments are translation, scale and rotation invariant. Wavelet analysis has the trait of multi-resolution analysis, which strengthens the analysis ability to image subtle feature. According with the psychol...

Abstract We establish the asymptotics of joint moments characteristic polynomial a random unitary matrix and its derivative for general real values exponents, proving conjecture made by Hughes [ 40] in 2001. Moreover, we give probabilistic representation leading order coefficient asymptotic terms real-valued variable that plays an important role ergodic decomposition Hua–Pickrell measures. This...

One of the most important prediction problems in finite population is the prediction of a linear function of characteristic values of a finite population. In this paper the admissibility of linear predictors of an arbitrary linear function of characteristic values in a finite population under reflected normal loss function is considered. Under the super-population model, we obtain the condition...

Abstract The Lindley distribution has been generalized by several researchers in recent years. In this paper, we introduce and study a new generalization of extended power named alpha transformed ( APTEPL ) that provides better fits than the Power existing generalizations. It includes Lindley, as special cases. article various properties such moments, moment generating function, Characteristic ...