Restricted Tweedie stochastic block models
Canadian Journal of Statistics, EarlyView.Abstract The stochastic block model (SBM) is a widely used framework for community detection in networks, where the network structure is typically represented by an adjacency matrix. However, conventional SBMs are not directly applicable to an adjacency matrix that consists of nonnegative zero‐inflated continuous edge weights.
Jie Jian, Mu Zhu, Peijun Sang
wiley +1 more source
Neural variability in the default mode network compresses with increasing belief precision during Bayesian inference. [PDF]
Cereb CortexSkowron A +5 more
europepmc +1 more source
Rank‐based estimation of propensity score weights via subclassification
Canadian Journal of Statistics, EarlyView.Abstract Propensity score (PS) weighting estimators are widely used for causal effect estimation and enjoy desirable theoretical properties, such as consistency and potential efficiency under correct model specification. However, their performance can degrade in practice due to sensitivity to PS model misspecification.
Linbo Wang +3 more
wiley +1 more source
Bayesian inference of nosocomial meticillin-resistant Staphylococcus aureus transmission rates in an urban safety-net hospital. [PDF]
J Hosp InfectCorkran K +4 more
europepmc +1 more source
Canadian Journal of Statistics, EarlyView.Abstract We establish the consistency and the asymptotic distribution of the least squares estimators of the coefficients of a subset vector autoregressive process with exogenous variables (VARX). Using a martingale central limit theorem, we derive the asymptotic normal distribution of the estimators. Diagnostic checking is discussed using kernel‐based
Pierre Duchesne +2 more
wiley +1 more source
Random time-shift approximation enables hierarchical Bayesian inference of mechanistic within-host viral dynamics models on large datasets. [PDF]
PLoS Comput BiolMorris DJ, Kennedy L, Black AJ.
europepmc +1 more source
Hidden Markov graphical models with state‐dependent generalized hyperbolic distributions
Canadian Journal of Statistics, EarlyView.Abstract In this article, we develop a novel hidden Markov graphical model to investigate time‐varying interconnectedness between different financial markets. To identify conditional correlation structures under varying market conditions and accommodate shape features embedded in financial time series, we rely upon the generalized hyperbolic family of ...
Beatrice Foroni +2 more
wiley +1 more source
Partial identification with categorical data and nonignorable missing outcomes
Canadian Journal of Statistics, EarlyView.Abstract Nonignorable missing outcomes are common in real‐world datasets and often require strong parametric assumptions to achieve identification. These assumptions can be implausible or untestable, and so we may wish to forgo them in favour of partially identified models that narrow the set of a priori possible values to an identification region.
Daniel Daly‐Grafstein, Paul Gustafson
wiley +1 more source
ScITree: Scalable Bayesian inference of transmission tree from epidemiological and genomic data. [PDF]
PLoS Comput BiolWaddel H, Koelle K, Lau MSY.
europepmc +1 more source