Export 1625 results:
Factor copula models for data with spatio-temporal dependence. Spatial Statistics, 22(1), pp.180-195., 2017.
On finite mixture models. Statistical Theory and Related Fields, 1, pp.15–27., 2017.
Flexible Correlation Structure for Accurate Prediction and Uncertainty Quantification in Bayesian Gaussian Process Emulation of a Computer Model. SIAM/ASA Journal on Uncertainty Quantification, 5(1), p.620. Available at: http://epubs.siam.org/doi/abs/10.1137/15M1008774., 2017.
Flexible Correlation Structure for Accurate Prediction and Uncertainty Quantification in Bayesian Gaussian Process Emulation of a Computer Model. SIAM/ASA Journal on Uncertainty Quantification, 5, pp.598–620. Available at: https://doi.org/10.1137/15M1008774., 2017.
Health-care use before a first demyelinating event suggestive of a multiple sclerosis prodrome: a matched cohort study. The Lancet Neurology, 16, pp.445–451., 2017.
Hepatitis C cross-genotype immunity and implications for vaccine development. Scientific reports, 7, p.12326., 2017.
Hypothesis testing in the presence of multiple samples under density ratio models. Statistica Sinica, 27, pp.716–783., 2017.
Identification of treatment responders based on multiple longitudinal outcomes with applications to multiple sclerosis patients. Statistics in Medicine, 36, pp.1862-1883., 2017.
Incidence, risk factors, and prevention of hepatitis C reinfection: a population-based cohort study. The Lancet Gastroenterology & Hepatology, 2, pp.200–210., 2017.
Model selection for discrete regular vine copulas. COMPUTATIONAL STATISTICS & DATA ANALYSIS, 106, pp.138-152., 2017.
Multi-tissue polygenic models for transcriptome-wide association studies. bioRxiv, p.107623., 2017.
Multivariate dependence modeling based on comonotonic factors. Journal of Multivariate Analysis, 155, pp.317-333., 2017.
Network meta-analysis of disconnected networks: How dangerous are random baseline treatment effects?. Research synthesis methods, 8, pp.465–474., 2017.
Parametric copula families for statistical models. In Copulas and Dependence Models with Applications: Contributions in Honor of Roger B. Nelsen. Copulas and Dependence Models with Applications: Contributions in Honor of Roger B. Nelsen. Berlin: Springer, pp. 119–134. Available at: https://link.springer.com/book/10.1007/978-3-319-64221-5., 2017.
Particle Gibbs split-merge sampling for Bayesian inference in mixture models. Journal of Machine Learning Research, 18, pp.1–39., 2017.
PGCA: An algorithm to link protein groups created from MS/MS data. PLOS ONE, 12, pp.1-19. Available at: https://doi.org/10.1371/journal.pone.0177569., 2017.
Piecewise Deterministic Markov Chain Monte Carlo. arXiv, 1707.05296., 2017.
A Poissonian model of indel rate variation for phylogenetic tree inference. Systematic Biology, (Accepted)., 2017.
A Poissonian model of indel rate variation for phylogenetic tree inference. Systematic Biology, 66, pp.698–714., 2017.
Pre-averaged kernel estimators for the drift function of a diffusion process in the presence of microstructure noise. Statistical Inference for Stochastic Processes, 20(2)., 2017.
Regularization in regime-switching Gaussian autoregressive models. The Canadian Journal of Statistics, 45, p.374., 2017.
ReMixT: clone-specific genomic structure estimation in cancer. Genome Biology, 18., 2017.