In this paper we propose a denoising methodology in the wavelet domain based on a Bayesian hierarchical model using Double Weibull prior. We propose two estimators, one based on posterior mean (DWWS ) and the other based on larger posterior mode (DWWSLPM ), and show how to calculate them efficiently. Traditionally, mixture priors have been used for modeling sparse wavelet coefficients. The inte...

Cure rate estimation is an important issue in clinical trials for diseases such as lymphoma and breast cancer and mixture models are the main statistical methods. In the last decade, mixture models under different distributions, such as exponential, Weibull, log-normal and Gompertz, have been discussed and used. However, these models involve stronger distributional assumptions than is desirable...

A new lifetime distribution capable of modeling a bathtub-shaped hazard-rate function is proposed. The proposed model is derived as a limiting case of the Beta Integrated Model and has both the Weibull distribution and Type I extreme value distribution as special cases. The model can be considered as another useful 3-parameter generalization of the Weibull distribution. An advantage of the mode...

Nowadays, the search for a distribution capable of modeling the probability density function (PDF) of irradiance data under all conditions of atmospheric turbulence in the presence of aperture averaging still continues. Here, a family of PDFs alternative to the widely accepted Log-Normal and Gamma-Gamma distributions is proposed to model the PDF of the received optical power in free-space optic...

Characterizing the wind speed distribution properly is essential for satisfactory production of potential energy in farms, being mixture models usually employed description such data. However, some commonly have undesirable property non-identifiability. In this work, we present an alternative which able to fit data decently. The new model, called Normal-Weibull-Weibull, identifiable and its cum...

Estimation of mixed Weibull distribution by maximum likelihood estimation and other methods is frequently difficult due to unstable estimates arising from limited data. Bayesian techniques can stabilize these estimates through the priors, but there is no closed-form conjugate family for the Weibull distribution. This paper reduces the number of numeric integrations required for using Bayesian e...

This study aims to compare the predictive capability of two popular software reliability growth models (SRGM), say exponential growth and inflection S-shaped growth models. We first review the exponentiated Weibull (EW) testing-effort functions and discuss exponential type and inflection S-shaped type SRGM with EW testing-effort. We then analyzed the actual data applications and compare the pre...

the data set employed in this study was comprised of a number of 6,800 records of lamb’s longevity and their survival rate, collected from 1989 through 2009, from the lori-bakhtiari experimental flock at the shooli station in shahrekord, iran. the data were analyzed using linear models and proportional hazard models with weibull function. these models included fixed factors and direct additive ...