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Modeling Waveform Shapes with Random Eects Segmental Hidden Markov Models
Modeling Waveform Shapes Random Eects Segmental Hidden Markov Models
2012/9/19
In this paper we describe a general probabilis-tic framework for modeling waveforms such as heartbeats from ECGdata. The model is based on segmental hidden Markov mod-els(as usedin speechrecognition) ...
Modeling Waveform Shapes with Random Eects Segmental Hidden Markov Models
Modeling Waveform Shapes Random Eects Segmental Hidden Markov Models
2012/9/19
In this paper we describe a general probabilis-tic framework for modeling waveforms such as heartbeats from ECGdata. The model is based on segmental hidden Markov mod-els(as usedin speechrecognition) ...
Consistency of M estimates for separable nonlinear regression models
Nonlinear regression separable models con-sistency robust estimation.
2012/9/18
Consider a nonlinear regression model :yi =g(xi, 兤) +ei, i = 1, ..., n,where thexi are random predictorsxi and兤is the unknown parameter vector ranging in a set set 儲伡Rp. All known results on the consi...
Statistical inference in compound functional models
Compound functional model minimax estimation sparse additive structure dimen-sion reduction structure adaptation
2012/9/18
We consider a general nonparametric regression model called the compound model. It includes,as special cases, sparse additive regression and nonparametric (or linear) regression with many covariates b...
TheMacaulay2packageGraphicalModelscontains algorithms for the algebraic study of graphical models associated to undirected, directed and mixed graphs, and associated collections of conditional indepen...
Mixture Models for Single Cell Assays with Applications to Vaccine Studies
Mixture Models Single Cell Assays Applications to Vaccine Studies
2012/9/18
Blood and tissue are composed of many functionally distinct cell subsets. In immunological studies, these can only be measured accurately using single-cell assays. The characterization of these small ...
A population Monte Carlo scheme with transformed weights and its application to stochastic kinetic models
Population Monte Carlo importance sampling degeneracy of importance weights stochastic kinetic models
2012/9/18
This paper addresses the problem of Monte Carlo approximation of posterior probability distributions. In particular, we have considered a recently proposed technique known as population Monte Carlo (P...
Penalized estimation in high-dimensional hidden Markov models with state-specific graphical models
HMM Graphical Lasso Universal Regularization Model Selection MMDL Greedy Backwards Pruning Genome Biology Chromatin Modeling
2012/9/17
We consider penalized estimation in hidden Markov models (HMMs) with multi-variate Normal observations. In the moderate-to-large dimensional setting, estimation for HMMs remains challenging in practic...
A stochastic variational framework for fitting and diagnosing generalized linear mixed models
Hierarchical model Identify divergent units Large longitudinal data Non-conjugate model Stochastic approximation Variational Bayes
2012/9/17
Variational Bayes computational methods are attracting increasing in-terest because of their ability to scale to large data sets. Here, application of the
non-conjugate variational message passing (N...
Accept & Reject Statement-Based Uncertainty Models
acceptability indifference desirability favourability preference prevision
2012/9/18
We develop a framework for modelling and reasoning with uncertainty based on accept and reject statements about gambles. It generalises the frameworks found in the literature based on statements of ac...
Composite likelihood estimation of sparse Gaussian graphical models with symmetry
Variable selection model selection penalized estimation Gaussian graphical model concentration matrix partial correlation matrix
2012/9/17
In this article, we discuss the composite likelihood estimation of sparse Gaussian graph-ical models. When there are symmetry constraints on the concentration matrix or partial correlation matrix, the...
Integrated analysis of variants and pathways in genome-wide association studies using polygenic models of disease
Integrated analysis of variants pathways genome-wide association studies polygenic models of disease
2012/9/18
Many common diseases are highly polygenic, modulated by a large number genetic factors with small effects on suscep-tibility to disease. These small effects are difficult to map reliably in genetic as...
Asymptotics for penalized splines in generalized additive models
Asymptotic normality B-spline Generalized additive model Mixed model Pe-nalized spline
2012/9/17
This paper discusses asymptotic theory for penalized spline estimators in generalized additive models. The purpose of this paper is to establish the asymptotic bias and variance as well as the asympto...
Nonconcave penalized composite conditional likelihood estimation of sparse Ising models
Composite likelihood coordinatewise optimization Ising model minorization–maximization principle NP-dimension asymptotic theory HIV drug resistance database.
2012/9/17
The Ising model is a useful tool for studying complex interactions within a system. The estimation of such a model, however, is rather challenging, especially in the presence of high-dimensional param...
Inference of time-varying regression models
Information criterion locally stationary processes nonpara-metric hypothesis testings time-varying coefficient models variable selection.
2012/9/17
We consider parameter estimation, hypothesis testing and vari-able selection for partially time-varying coefficient models. Our asymp-totic theory has the useful feature that it can allow dependent, n...