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Adapting the Stochastic Block Model to Edge-Weighted Networks
Adapting Stochastic Block Model Edge-Weighted Networks
2013/6/14
We generalize the stochastic block model to the important case in which edges are annotated with weights drawn from an exponential family distribution. This generalization introduces several technical...
A Bayesian localised conditional auto-regressive model for estimating the health effects of air pollution
Air pollution and health Conditional autoregressive models Spatial correlation
2013/6/14
Estimation of the long-term health effects of air pollution is a challenging task, especially when modelling small-area disease incidence data in an ecological study design. The challenge comes from t...
A Supervised Neural Autoregressive Topic Model for Simultaneous Image Classification and Annotation
ASupervised Neural Autoregressive Topic Model Simultaneous Image Classification Annotation
2013/6/17
Topic modeling based on latent Dirichlet allocation (LDA) has been a framework of choice to perform scene recognition and annotation. Recently, a new type of topic model called the Document Neural Aut...
A Penalized Multi-trait Mixed Model for Association Mapping in Pedigree-based GWAS
Multivariate linear mixed model Penalization approach Feature selection 1 arXiv:1305.4413v1 [stat.ME] 19 May 2013 GWAS
2013/6/14
In genome-wide association studies (GWAS), penalization is an important approach for identifying genetic markers associated with trait while mixed model is successful in accounting for a complicated d...
Does "model-free" forecasting really outperform the "true" model? A reply to Perretti et al
"model-free" forecasting outperform "true" model
2013/6/14
Estimating population models from uncertain observations is an important problem in ecology. Perretti et al. observed that standard Bayesian state-space solutions to this problem may provide biased pa...
A Gaussian Process Emulator Approach for Rapid Contaminant Characterization with an Integrated Multizone-CFD Model
xBayesian Framework Gaussian Process Emulator Multizone Models Integrated Multizone-CFD CONTAM Rapid Source Localization and Characterization
2013/6/14
This paper explores a Gaussian process emulator based approach for rapid Bayesian inference of contaminant source location and characteristics in an indoor environment. In the pre-event detection stag...
Inference and testing for structural change in time series of counts model
time series of counts Poisson autoregression likelihood estimation change-point semi-parametric test
2013/6/14
We consider here together the inference questions and the change-point problem in Poisson autoregressions (see Tj{\o}stheim, 2012). The conditional mean (or intensity) of the process is involved as a ...
Functional and Parametric Estimation in a Semi- and Nonparametric Model with Application to Mass-Spectrometry Data
Local linear regression Bandwidth selection Nonparamet-ric estimation
2013/6/13
Motivated by modeling and analysis of mass-spectrometry data, a semi- and nonparametric model is proposed that consists of a linear parametric component for individual location and scale and a nonpara...
Moment based estimation of supOU processes and a related stochastic volatility model
generalized method of moments Ornstein-Uhlenbeck type process L
2013/6/14
After a quick review of superpositions of OU (supOU) processes, integrated supOU processes and the supOU SV model we estimate these processes by using the generalized method of moments. We show that t...
Probabilistic wind speed forecasting using Bayesian model averaging with truncated normal components
Bayesian model averaging continuous ranked probability score ensemble calibration truncated normal distribution
2013/6/13
Bayesian model averaging (BMA) is a statistical method for post-processing forecast ensembles of atmospheric variables, obtained from multiple runs of numerical weather prediction models, in order to ...
Model-based dose finding under model uncertainty using general parametric models
Model-based model uncertainty parametric models
2013/6/13
Statistical methodology for the design and analysis of clinical Phase II dose response studies, with related software implementation, are well developed for the case of a normally distributed, homosce...
GPfit: An R package for Gaussian Process Model Fitting using a New Optimization Algorithm
Computer experiments, clustering, near-singularity, nugget
2013/6/13
Gaussian process (GP) models are commonly used statistical metamodels for emulating expensive computer simulators. Fitting a GP model can be numerically unstable if any pair of design points in the in...
Model Selection for High-Dimensional Regression under the Generalized Irrepresentability Condition
Model Selection High-Dimensional Regression Generalized Irrepresentability Condition
2013/6/13
In the high-dimensional regression model a response variable is linearly related to $p$ covariates, but the sample size $n$ is smaller than $p$. We assume that only a small subset of covariates is `ac...
Species dynamics in the two-parameter Poisson-Dirichlet diffusion model
alpha diversity infinite-alleles model infinite dimensional dimensional diffusion mutation rate Poisson-Dirichlet distribution weak convergence
2013/6/14
The recently introduced two-parameter infinitely-many neutral alleles model extends the celebrated one-parameter version, related to Kingman's distribution, to diffusive two-parameter Poisson-Dirichle...
Complexity penalized hydraulic fracture localization and moment tensor estimation under limited model information
Complexity penalized hydraulic fracture localization moment tensor estimation limited model information
2013/6/14
In this paper we present a novel technique for micro-seismic localization using a group sparse penalization that is robust to the focal mechanism of the source and requires only a velocity model of th...