Considering that power consumption (PC) is an extremely important indicator in digital circuit design, lower PC has always been our pursuit. and supply voltage are positively correlated, this case, we must reduce the operating of circuit. However, as continues to decrease, various secondary effects process variations become increasingly influential, making delay distribution its statistical cha...

Stock prices are known to exhibit non-Gaussian dynamics, and there is much interest in understanding the origin of this behavior. Here, we present a model that explains the shape and scaling of the distribution of intraday stock price fluctuations (called intraday returns) and verify the model using a large database for several stocks traded on the London Stock Exchange. We provide evidence tha...

In the present article we derive a new discrete multivariate distribution using a limiting argument that is essentially the same as the law of small numbers. The distribution derived belongs to an exponential family, and randomly partitions positive integers. The facts shown about the distribution are useful in many fields of application involved with count data. The derivation parallels that o...

   In This paper, the effect of size on melting temperature of metallic nanoparticles (Au, Pb and Bi) is theoretically simulated and explained. In this regard, the cause of difference in various experimental data is introduced, which is the difference between nanoparticles’ grain Gaussian distribution. This volume-depended model with the help of the Gaussian distribution can descri...

The dependence between individuals in a group is modeled by the group specific quantity, which can be interpreted as an unobserved covariates or “frailties” common to the individuals in the group and assumed to follow some distribution. We consider the shared frailty model in the frame work of parametric Cox proportional hazard model. The Cox regression model with the shared frailty factor allo...

This paper conducts a Bayesian analysis of inverse Gaussian process models for degradation modeling and inference. Novel features of the Bayesian analysis are the natural manners for incorporating subjective information, pooling of random effects information among product population, and a straightforward way of coping with evolving data sets for on-line prediction. A general Bayesian framework...

EXAFS spectra for all K absorption edges and X-ray scattering data have been obtained on an amorphous Fe-Zr sample prepared by mechanical alloying and a rapidly quenched Co-Zr one. Partial pair distribution fnnctions have been determined as a solution of an inverse ill-posed problem for the system of integral equations describing combined experimental data. For Fe-Zr and Ca-Zr amorphous alloys ...

We propose a new procedure to perform Reduced Rank Regression (RRR) in nonGaussian contexts, based on Multivariate Dispersion Models. Reduced-Rank Multivariate Dispersion Models (RR-MDM) generalise RRR to a very large class of distributions, which include continuous distributions like the normal, Gamma, Inverse Gaussian, and discrete distributions like the Poisson and the binomial. A multivaria...