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Joint Modeling and Clustering Paired Generalized Longitudinal Trajectories with Application to Cocaine Abuse Treatment Data
Clustering Functional data analysis Exponential family Joint modeling
2016/1/26
In a cocaine dependence treatment study, we have paired binary longitudinal tra-jectories that record the cocaine use patterns of each patient before and after a treat-ment. To better understand the d...
Poisson-PDNN: Modeling non-uniform read distribution in RNA-seq data
Poisson-PDNN Modeling non-uniform distribution in RNA-seq data
2016/1/25
RNA-Seq is a powerful new technology to comprehensively analyze the transcriptome of any given cells. An important task in RNA-Seq data analysis is quantifying the expression levels of all transcripts...
Joint Modeling and Clustering Paired Generalized Longitudinal Trajectories with Application to Cocaine Abuse Treatment Data
Clustering functional data analysis exponential family joint modeling EM algorithm
2016/1/20
In a cocaine dependence treatment study, we have paired binary longitudinal tra-jectories that record the cocaine use patterns of each patient before and after a treat-ment. To better understand the d...
Poisson-PDNN: Modeling non-uniform read distribution in RNA-seq data
Poisson-PDNN Modeling non-uniform distribution RNA-seq data
2016/1/20
RNA-Seq is a powerful new technology to comprehensively analyze the transcriptome of any given cells. An important task in RNA-Seq data analysis is quantifying the expression levels of all transcripts...
Discrete Breathers in a Forced-Damped Array of Coupled Pendula: Modeling, Computation, and Experiment
Machinery the localization model enhance the liquidity local mode damping coupling
2014/12/24
In this work, we present a mechanical example of an experimental realization of a stability reversal between on-site and intersite centered localized modes. A corresponding realization of a vanishing ...
Adapting the Interrelated Two-way Clustering method for Quantitative Structure-Activity Relationship (QSAR) Modeling of a Diverse Set of Chemical Compounds
Mutagenicity topological indices atom pairs Interrelated Two-way Clustering ridge regression quantum chemical descriptors
2013/6/14
Interrelated Two-way Clustering (ITC) is an unsupervised clustering method developed to divide samples into two groups in gene expression data obtained through microarrays, selecting important genes s...
Joint Modeling and Registration of Cell Populations in Cohorts of High-Dimensional Flow Cytometric Data
Joint Modeling Registration Cell Populations Cohorts High-Dimensional Flow Cytometric Data
2013/6/14
In systems biomedicine, an experimenter encounters different potential sources of variation in data such as individual samples, multiple experimental conditions, and multi-variable network-level respo...
Bayesian Multi-Dipole Modeling of Single MEG Topographies by Adaptive Sequential Monte Carlo Samplers
Magnetoencephalography inverse problem Multi-object estimation Multi-dipole models Adaptive Sequential Monte Carlo samplers
2013/6/14
We describe a novel Bayesian approach to the estimation of neural currents from a single distribution of magnetic field, measured by magnetoencephalography. We model neural currents as an unknown numb...
Modeling Information Propagation with Survival Theory
Modeling Information Propagation Survival Theory
2013/6/14
Networks provide a skeleton for the spread of contagions, like, information, ideas, behaviors and diseases. Many times networks over which contagions diffuse are unobserved and need to be inferred. He...
Modeling Temporal Activity Patterns in Dynamic Social Networks
Activity Profile Modeling Twitter Data-Fitting Explanation Prediction Hidden Markov Model Coupled Hidden Markov Model Social Network In uence User Clustering
2013/6/14
The focus of this work is on developing probabilistic models for user activity in social networks by incorporating the social network influence as perceived by the user. For this, we propose a coupled...
Joint Topic Modeling and Factor Analysis of Textual Information and Graded Response Data
Factor analysis topic model personalized learning machine learning block coordinate descent
2013/6/14
Modern machine learning methods are critical to the development of large-scale personalized learning systems that cater directly to the needs of individual learners. The recently developed SPARse Fact...
Bayesian Modeling and MCMC Computation in Linear Logistic Regression for Presence-only Data
Bayesian modeling case-control design data augmentation logistic regres-sion Markov Chain Monte Carlo population prevalence presence-only data simulation
2013/6/13
Presence-only data are referred to situations in which, given a censoring mechanism, a binary response can be observed only with respect to on outcome, usually called \textit{presence}. In this work w...
Robots rely on sensors to provide them with information about their surroundings. However, high-quality sensors can be extremely expensive and cost-prohibitive. Thus many robotic systems must make due...
Two General Methods for Population Pharmacokinetic Modeling: Non-Parametric Adaptive Grid and Non-Parametric Bayesian
Population pharmacokinetic modeling non-parametric maximum likelihood Bayesian Stick-breaking Pmetrics RJags
2013/5/2
Population pharmacokinetic (PK) modeling methods can be statistically classified as either parametric or nonparametric (NP). Each classification can be divided into maximum likelihood (ML) or Bayesian...
Modeling US house prices by spatial dynamic structural equation models
house prices Bayesian inference dynamic factor models spatio-temporal models cointegration lattice data
2013/4/27
This article proposes a spatial dynamic structural equation model for the analysis of housing prices at the State level in the USA. The study contributes to the existing literature by extending the us...