A number of approaches have been developed for analyzing incident clearance time data and investigating the effects of different explanatory variables on clearance time. Among these methods, hazard-based duration models (i.e., proportional hazard and accelerated failure time models) have been extensively used. The finite mixture model is an alternative approach in survival data analysis, and of...

Automatic speech recognition (ASR) systems usually consist of an acoustic model and a language model. This paper describes a technique of an efficient deployment of the acoustic model parameters. The acoustic model typically utilizes Continuous Density Hidden Markov Models (CDHMM). The output probability of a particular CDHMM state is represented by a Gaussian mixture density with a diagonal co...

In this paper we address the problem of estimating the parameters of a Gaussian mixture model. Although the EM (ExpectationMaximization) algorithm yields the maximum-likelihood solution it requires a careful initialization of the parameters and the optimal number of kernels in the mixture may be unknown beforehand. We propose a criterion based on the entropy of the pdf (probability density func...

We present a joint mixture model for integrating anatomical information in ECT reconstruction. The mixture model acts as a Bayesian prior with the added benefit of the anatomical segmentation pixel-region labels guiding the reconstruction process. An additional hyper-prior on the mixture occupation probability is introduced. This has the novel interpretation of maximizing the mutual information...

diagnosis of corneal diseases is possible by measuring and evaluation of corneal thickness in different layers. thus, the need for precise segmentation of corneal layer boundaries is inevitable. obviously, manual segmentation is time‑consuming and imprecise. in this paper, the gaussian mixture model (gmm) is used for automatic segmentation of three clinically important corneal boundaries on opt...

background : so far, several studies were conducted to estimate the prevalence of cigarette smoking in iran, but none of them used a statistical model to deal with unobserved smokers. the present study planned to estimate the accurate prevalence of cigarette smoking using mixture of truncated poisson distribution. methods : a cross-sectional study was conducted in hamadan, west of iran in 2009,...

background: the two most frequently diagnosed cancers among women worldwide are breast and cervical cancers. the objective of the present study was to classify the different countries based on the death rates from sex specific cancers. methods : in this cross-sectional study, we used dataset regarding death rate from breast, cervical, uterine, and ovarian cancers in 190 countries worldwide repo...

in a voice conversion system speech signal of a speaker (i.e. source speaker) is modified so that it sounds as if it had been pronounced by b speaker (i.e. target speaker). this process, sometimes, is called speaker conversion (changing speaker identity). achieved signal from speaker conversion system is desired to have high quality and very natural. to satisfy this, three major methods are pro...

In binary-transaction data-mining, traditional frequent itemset mining often produces results which are not straightforward to interpret. To overcome this problem, probability models are often used to produce more compact and conclusive results, albeit with some loss of accuracy. Bayesian statistics have been widely used in the development of probability models in machine learning in recent yea...