Preterm birth, defined as delivery before 37 completed weeks' gestation, is a leading cause of infant morbidity and mortality. Identifying factors related to preterm delivery is an important goal of public health professionals who wish to identify etiologic pathways to target for prevention. Validation studies are often conducted in nutritional epidemiology in order to study measurement error i...

This work presents an approach for signal/image denoising in a semi-parametric frame. Our model is a wavelet-based one, which essentially assumes a minimal local regularity. This assumption translates into constraints on the multifractal spectrum of the signals. Such constraints are in turn used in a Bayesian framework to estimate the wavelet coefficients of the original signal from the noisy o...

The probabilistic framework of extreme value theory is well-known: the dependence structure of large events is characterized by an angular measure on the positive orthant of the unit sphere. The family of these angular measures is non-parametric by nature. Nonetheless, any angular measure may be approached arbitrarily well by a mixture of Dirichlet distributions. The semi-parametric Dirichlet m...

One can fruitfully approach survival problems without covariates in an actuarial way. In narrow time bins, the number of people at risk is counted together with the number of events. The relationship between time and probability of an event can then be estimated with a parametric or semi-parametric model. The number of events observed in each bin is described using a Poisson distribution with t...

to evaluate genotype × environment interaction (gei) of grapevine, 20 genotypes of grapevines with russian origin were evaluated at one location in urmia and four locations in takestan (two locations under full irrigation and two locations under drought stress). this research was performed in a randomized complete block design with three replications and three vines in each plot, in 2012-2013 s...

This thesis is divided in two distinct parts. In the first part we are concerned with developing new statistical methodology for drawing Bayesian inference for partially observed stochastic epidemic models. In the second part, we develop a novel methodology for constructing a wide class of semi−parametric time series models. First, we introduce a general framework for the heterogeneously mixing...

With the exception of Bayesian analysis, phylogenetic inference procedures typically identify a best estimate of phylogenetic relationships, a so called point estimate of the phylogeny. However, the point estimate is often relatively uninteresting in itself unless we have some measure of its reliability. This lecture will be about techniques for examining the robustness or significance of the r...

This paper proposes a novel insight to the problem of duration modeling for Information Retrieval problems where a discrete sequence of events is estimated from a time-signal using Bayesian models. Since the duration of each event is unknown, a major issue is setting the right Bayesian prior on each of them. Hidden Semi-Markov models (HSMM) allow choosing explicitly any probability distribution...

The first issue is whether one ought to use of Bayesian or Classical methods of inference. I will briefly cover Bayesian methods which have been revitalized given recent developments in monte carlo simulation and numerical integration. Nevertheless, Bayesian methods are still computationally burdensome and heavily linked to particular parametric functional forms, limiting their applicability to...