Search results for " Statistical"
showing 10 items of 1649 documents
Bayesian hierarchical Poisson models with a hidden Markov structure for the detection of influenza epidemic outbreaks
2015
Considerable effort has been devoted to the development of statistical algorithms for the automated monitoring of influenza surveillance data. In this article, we introduce a framework of models for the early detection of the onset of an influenza epidemic which is applicable to different kinds of surveillance data. In particular, the process of the observed cases is modelled via a Bayesian Hierarchical Poisson model in which the intensity parameter is a function of the incidence rate. The key point is to consider this incidence rate as a normal distribution in which both parameters (mean and variance) are modelled differently, depending on whether the system is in an epidemic or non-epide…
Bayesian Markov switching models for the early detection of influenza epidemics
2008
The early detection of outbreaks of diseases is one of the most challenging objectives of epidemiological surveillance systems. In this paper, a Markov switching model is introduced to determine the epidemic and non-epidemic periods from influenza surveillance data: the process of differenced incidence rates is modelled either with a first-order autoregressive process or with a Gaussian white-noise process depending on whether the system is in an epidemic or in a non-epidemic phase. The transition between phases of the disease is modelled as a Markovian process. Bayesian inference is carried out on the former model to detect influenza epidemics at the very moment of their onset. Moreover, t…
Tailoring sparse multivariable regression techniques for prognostic single-nucleotide polymorphism signatures.
2011
When seeking prognostic information for patients, modern technologies provide a huge amount of genomic measurements as a starting point. For single-nucleotide polymorphisms (SNPs), there may be more than one million covariates that need to be simultaneously considered with respect to a clinical endpoint. Although the underlying biological problem cannot be solved on the basis of clinical cohorts of only modest size, some important SNPs might still be identified. Sparse multivariable regression techniques have recently become available for automatically identifying prognostic molecular signatures that comprise relatively few covariates and provide reasonable prediction performance. For illus…
Stochastic resonance and noise delayed extinction in a model of two competing species
2003
We study the role of the noise in the dynamics of two competing species. We consider generalized Lotka-Volterra equations in the presence of a multiplicative noise, which models the interaction between the species and the environment. The interaction parameter between the species is a random process which obeys a stochastic differential equation with a generalized bistable potential in the presence of a periodic driving term, which accounts for the environment temperature variation. We find noise-induced periodic oscillations of the species concentrations and stochastic resonance phenomenon. We find also a nonmonotonic behavior of the mean extinction time of one of the two competing species…
Bayesian survival analysis with BUGS
2020
Survival analysis is one of the most important fields of statistics in medicine and biological sciences. In addition, the computational advances in the last decades have favored the use of Bayesian methods in this context, providing a flexible and powerful alternative to the traditional frequentist approach. The objective of this article is to summarize some of the most popular Bayesian survival models, such as accelerated failure time, proportional hazards, mixture cure, competing risks, multi-state, frailty, and joint models of longitudinal and survival data. Moreover, an implementation of each presented model is provided using a BUGS syntax that can be run with JAGS from the R programmin…
Trading leads to scale-free self-organization
2009
Financial markets display scale-free behavior in many different aspects. The power-law behavior of part of the distribution of individual wealth has been recognized by Pareto as early as the nineteenth century. Heavy-tailed and scale-free behavior of the distribution of returns of different financial assets have been confirmed in a series of works. The existence of a Pareto-like distribution of the wealth of market participants has been connected with the scale-free distribution of trading volumes and price-returns. The origin of the Pareto-like wealth distribution, however, remained obscure. Here we show that it is the process of trading itself that under two mild assumptions spontaneously…
Adaptive linear rank tests for eQTL studies
2012
Expression quantitative trait loci (eQTL) studies are performed to identify single-nucleotide polymorphisms that modify average expression values of genes, proteins, or metabolites, depending on the genotype. As expression values are often not normally distributed, statistical methods for eQTL studies should be valid and powerful in these situations. Adaptive tests are promising alternatives to standard approaches, such as the analysis of variance or the Kruskal-Wallis test. In a two-stage procedure, skewness and tail length of the distributions are estimated and used to select one of several linear rank tests. In this study, we compare two adaptive tests that were proposed in the literatur…
A weighted combined effect measure for the analysis of a composite time-to-first-event endpoint with components of different clinical relevance
2018
Composite endpoints combine several events within a single variable, which increases the number of expected events and is thereby meant to increase the power. However, the interpretation of results can be difficult as the observed effect for the composite does not necessarily reflect the effects for the components, which may be of different magnitude or even point in adverse directions. Moreover, in clinical applications, the event types are often of different clinical relevance, which also complicates the interpretation of the composite effect. The common effect measure for composite endpoints is the all-cause hazard ratio, which gives equal weight to all events irrespective of their type …
A form factor approach to the asymptotic behavior of correlation functions in critical models
2011
We propose a form factor approach for the computation of the large distance asymptotic behavior of correlation functions in quantum critical (integrable) models. In the large distance regime we reduce the summation over all excited states to one over the particle/hole excitations lying on the Fermi surface in the thermodynamic limit. We compute these sums, over the so-called critical form factors, exactly. Thus we obtain the leading large distance behavior of each oscillating harmonic of the correlation function asymptotic expansion, including the corresponding amplitudes. Our method is applicable to a wide variety of integrable models and yields precisely the results stemming from the Lutt…
Thermal form factors of the XXZ chain and the large-distance asymptotics of its temperature dependent correlation functions
2013
We derive expressions for the form factors of the quantum transfer matrix of the spin-1/2 XXZ chain which are suitable for taking the infinite Trotter number limit. These form factors determine the finitely many amplitudes in the leading asymptotics of the finite-temperature correlation functions of the model. We consider form-factor expansions of the longitudinal and transversal two-point functions. Remarkably, the formulae for the amplitudes are in both cases of the same form. We also explain how to adapt our formulae to the description of ground state correlation functions of the finite chain. The usefulness of our novel formulae is demonstrated by working out explicit results in the hig…