Moments and transforms are the scalar quantities that characterise a function and capture its significant properties. More specifically, these are the descriptors that correspond to the projection of the function on a specific basis function, where the type or characteristic of the basis function gives the name to the moment or transform [82]. Normally, moments and transforms are treated separa...

Hybrid Euler-Hadamard products have previously been studied for the Riemann zeta function on its critical line and for Dirichlet Lfunctions in the context of the calculation of moments and connections with Random Matrix Theory. According to the Katz-Sarnak classification, these are believed to represent families of L-function with unitary symmetry. We here extend the formalism to families with ...

Abstract In this paper we consider a generalization of log-transformed version the inverse Weibull distribution. Several theoretical properties distribution are studied in detail including expressions for its probability density function, reliability hazard rate quantile characteristic raw moments, percentile measures, entropy median, mode etc. Certain structural along with measures as well and...

This article derives the probability density function (pdf) of the sum of a normal random variable and a (sphered) Student’s-t distribution on odd degrees of freedom greater than or equal to three. Apart from its intrinsic interest applications of this result include Bayesian wavelet shrinkage, Bayesian posterior density derivations, calculations in the theoretical analysis of projection indice...

In recent decades, studying order statistics arising from independent and not necessary identically distributed (INID) random variables has been a main concern for researchers. A cumulative distribution function (CDF) of these random variables (Fi:n) is a complex manipulating, long time consuming and a software-intensive tool that takes more and more times. Therefore, obtaining approximations a...

The higher-order characteristic basis function method (HO-CBFM) is clearly formulated. HO-CBFM provides results accurately even if a block division is arbitrary. The HO-CBFM combined with a volume integral equation (VIE) is used in the analysis of various antennas in the vicinity of a dielectric object. The results of the numerical analysis show that the HO-CBFM can reduce the CPU time while st...

In a recent article we have discussed the connections between averages of powers of Riemann’s ζ-function on the critical line, and averages of characteristic polynomials of random matrices. The result for random matrices was shown to be universal, i.e. independent of the specific probability distribution, and the results were derived for arbitrary moments. This allows one to extend the previous...

In this paper, the multilinear normal distribution is introduced as an extension of the matrix-variate normal distribution. Basic properties such as marginal and conditional distributions, moments, and the characteristic function, are also presented. The estimation of parameters using a flip-flop algorithm is also briefly discussed.

The end-to-end performance of multibranch dual-hop wireless communication systems with nonregenerative relays and equal gain combiner (EGC) at the destination over independent Nakagami-m fading channels is studied. We present new closed form expressions for probability distribution function (PDF) and cumulative distribution function (CDF) of end-to-end signal to noise ratio (SNR) per branch in ...

The scope of this paper is to present a wavelet-based technique aimed at determining the range of existence for the moments of arbitrary random variables. Our work relies on the characterization of the local Hölder regularity of the characteristic function, as an indicator of the interval bounds under interest. Our motivation stems from multifractal analysis of processes.