In recent decades, there have been numerous endeavors to develop a novel category of survival distributions possessing enhanced flexibility through the extension existing distributions. This article constructs and validates statistical properties distribution in order obtain an alternative that is suitable for analyzing data by presenting mixture Fréchet along with such as probability density f...

We propose the exact calculation of the probability density function (PDF) and cumulative distribution function (CDF) of mutual information (MI) for a two-user MIMO MAC network over block Rayleigh fading channels. So far the PDF and CDF have been numerically evaluated since MI depends on the quotient of two Wishart matrices, and no closed-form for this quotient was available. We derive exact re...

The uniformly minimum variance unbiased (UMVU), maximum likelihood, percentile (PC), least squares (LS) and weighted least squares (WLS) estimators of the probability density function (pdf) and cumulative distribution function are derived for the generalized Rayleigh distribution. This model can be used quite effectively in modelling strength data and also modeling general lifetime data. It has...

The theoretical analysis of the peak-to-average power ratio (PAPR) distribution for an orthogonal frequency division multiplexing (OFDM) system, depends on the particular waveform considered in the modulation system. In this paper, we generalize this analysis by considering the generalized waveforms for multi-carrier (GWMC) modulation system based on any family of modulation functions, and we d...

This research estimates portfolio VaR (Value-at-Risk) on G7 exchange rates using a GJR-GARCH-EVT (extreme value theory)-Copula based approach. We first extracts the filtered residuals from each return series via an asymmetric GJR-GARCH model, then constructs the semi-parametric empirical marginal cumulative distribution function (CDF) of each asset using a Gaussian kernel estimate for the inter...

Abstract Deep neural networks (DNNs) and auto differentiation have been widely used in computational physics to solve variational problems. When a DNN is represent the wave function quantum many-body problems using optimization, various physical constraints be injected into network by construction increase data learning efficiency. We build unitary constraint monotonic cumulative distribution (...

This paper introduces a new constraint domain for reasoning about data with uncertainty. It extends convex modeling with the notion of p-box to gain additional quantifiable information on the data whereabouts. Unlike existing approaches, the p-box envelops an unknown probability instead of approximating its representation. The p-box bounds are uniform cumulative distribution functions (cdf) in ...

Reliability is one of the main indicators structural elements mechanical safety. The choice stochastic models an important task in reliability analysis for describing variability random variables with aleatory and epistemic uncertainty. article proposes a method RHS (rectangular hollow sections) steel truss joints based on p-boxes approach. consist two boundary distribution functions that creat...

Abstract Following the results of a study carried out for the neighbouring Sicilian region, this paper reports a study of the applicability of the annual value, F , of the Arnouldus index to represent the erosion risk in Calabrian region. Firstly, By using 214 values of the mean annual value of the erosivity index, FF, and a Kriging interpolation method, an isoerosivity map is plotted. Then, in...