Wind speed is the most important parameter in the design and study of the environmental impact assessment. The wind speed determines the concentration of any toxic pollutant released from any chemical industry. As the wind speed increases the concentration of the toxic pollutant at any location in the environment at any instant of time decreases. It is also known that as the wind speed increase...

The Weibull distribution is a very applicable model for the lifetime data. For inference about two Weibull distributions using records, the shape parameters of the distributions are usually considered equal. However, there is not an appropriate method for comparing the shape parameters in the literature. Therefore, comparing the shape parameters of two Weibull distributions is very important. I...

Several characterizations of a New Modified Weibull distribution, introduced by Doostmoradi et al. (2014), are presented. These characterizations are based on: (i) truncated moment of a function of the random variable (ii) the hazard function (iii) a single function of the random variable (iv) truncated moment of certain function of the 1st order statistic.

In many pharmaceutical studies, non-inferiority clinical trials are usually conducted because of the difficulty of finding a therapy that has more superior efficacy than a recognized effective one. When planning the non-inferiority clinical trials with a time-to-event endpoint, the calculation of sample size is one of the most fundamental steps. A proper sample size provides reasonable power to...

For Modified-Weibull distribution we have obtained the Bayes Estimators of scale and shape parameters using Lindley's approximation (L-approximation) under various loss functions. The proposed estimators have been compared with the corresponding MLE for their risks based on corresponding simulated samples. Key-Words: Bayesian estimation, Lindley's approximation, Maximum likelihood estimates, Mo...

To train an inference network jointly with a deep generative topic model, making it both scalable to big corpora and fast in out-of-sample prediction, we develop Weibull hybrid autoencoding inference (WHAI) for deep latent Dirichlet allocation, which infers posterior samples via a hybrid of stochastic-gradient MCMC and autoencoding variational Bayes. The generative network of WHAI has a hierarc...

In diseases caused by a deleterious gene mutation, knowledge of age-specific cumulative risks is necessary for medical management of mutation carriers. When pedigrees are ascertained through at least one affected individual, ascertainment bias can be corrected by using a parametric method such as the Proband's phenotype Exclusion Likelihood, or PEL, that uses a survival analysis approach based ...