Multi-type recurrent events are often encountered in medical applications when two or more different event types could repeatedly occur over an observation period. For example, patients may experience recurrences of multi-type nonmelanoma skin cancers a clinical trial for cancer prevention. The aims those to characterize features the marginal processes, evaluate covariate effects, and quantify ...

صفحه‌­ی مینیاتوری LEU پرتودهی شده در رآکتور تحقیقاتی تهران که برای تولید رادیوایزوتوپ مولیبدن-99 استفاده می‌شود، منبع پرتوزایی متشکل از رادیوایزوتوپ‌های مختلف است. محاسبه و تخمین آهنگ دز تابش‌های گامای گسیلی این منبع، به منظور مقایسه با مقادیر مجاز توصیه حمل‌ونقل مواد پرتوزا حفاظت پرتویی کارکنان حین انجام تست‌های آزمایشگاهی داغ، پیش هر اقدام عملی، امری ضروری مقاله، اعتبار یک روش پیشنهادی جهت هد...

We have previously shown how to perform inference about symmetric stable processes using Monte Carlo EM (MCEM) and Markov chain Monte Carlo (MCMC) techniques. Simulation based methods such as these are an excellent tool for inference with stable law distributions, since they do not require any direct evaluation of the stable density function, which is unavailable analytically in the general cas...

When making predictions with complex simulators it can be important to quantify the various sources of uncertainty. Errors in the structural specification of the simulator, for example due to missing processes or incorrect mathematical specification, can be a major source of uncertainty, but are often ignored. We introduce a methodology for inferring the discrepancy between the simulator and th...

A deep generative model is developed for representation and analysis of images, based on a hierarchical convolutional dictionary-learning framework. Stochastic unpooling is employed to link consecutive layers in the model, yielding top-down image generation. A Bayesian support vector machine is linked to the top-layer features, yielding max-margin discrimination. Deep deconvolutional inference ...

The analysis of finite mixture models for exponential repeated data is considered. The mixture components correspond to different unknown groups of the statistical units. Dependency and variability of repeateddata are taken into account through randomeffects. For each component, an exponential mixed model is thus defined. When considering parameter estimation in this mixture of exponential mixe...

We propose a standard approach to make inference for spatial generalized linear mixed models using Laplace approximation. Based on analysis of two datasets previous analysed in literature, we compare our approach with different approaches. The first the rhizoctonia root rot dataset is an example of Binomial SGLMM and the second rongelap dataset is an example of Poisson or Negative Binomial SGLM...

Methods Design: Prospective observational study Setting: Pediatric Emergency Department (ED) of a Community Hospital with 10500 ED visits annually. The hospital conducts DNB Pediatrics, MCEM and BSc Accident & Emergency Technology courses. Participants: 3693 children between 0 and 18 years of age who attended ED in a six month period from September 2011 to February 2012 Tools: Nurses on triage ...

Recently, it is recognized that nonlinear relationships among latent variables in a structural equation model are important. In this article, maximum likelihood (ML) analysis of a general nonlinear structural equation model that contains 5xed covariates in the measurement equation and the nonlinear structural equation is investigated. A MCEM algorithm is implemented to obtain the ML estimates, ...

The low-voltage efficiency of the blue-emitting phosphor, cerium activated yttrium silicate (Y1 mCem)2SiO5, has been improved by co-activating with gadolinium, (Y1 m nCemGdn)2SiO5. Gd 3+ improves the efficiency by transferring energy to Ce, and makes this phosphor a more promising candidate for low-voltage field emission flat panel displays. Low-voltage cathodoluminescence and photoluminescence...