Results 211 to 220 of about 21,998,513 (385)
Hierarchical non-emitting Markov models [PDF]
, 1997 Eric Sven Ristad, Robert G. Thomas
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Hidden Markov model approach to skill learning and its application to telerobotics [PDF]
, 1994 Jie Yang, Yangsheng Xu, C.S. Chen
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Fast and scalable inference for spatial extreme value models
Canadian Journal of Statistics, EarlyView.Abstract The generalized extreme value (GEV) distribution is a popular model for analyzing and forecasting extreme weather data. To increase prediction accuracy, spatial information is often pooled via a latent Gaussian process (GP) on the GEV parameters. Inference for GEV‐GP models is typically carried out using Markov Chain Monte Carlo (MCMC) methods,
Meixi Chen, Reza Ramezan, Martin Lysy
wiley +1 more source
Hematological Oncology, Volume 40, Issue 5, Page 987-998, December 2022., 2022 Abstract The treatment scenario for newly‐diagnosed transplant‐ineligible multiple myeloma patients (NEMM) is quickly evolving. Currently, combinations of proteasome inhibitors and/or immunomodulatory drugs +/− the monoclonal antibody Daratumumab are used for first‐line treatment, even if head‐to‐head comparisons are lacking.
Cirino Botta +17 more
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Correction: Deterministic and Probabilistic Analysis of a Simple Markov Model: How Different Could They Be? [PDF]
Appl Health Econ Health Policy, 2023 Thom H.
europepmc +1 more source
Robust causal inference for point exposures with missing confounders
Canadian Journal of Statistics, EarlyView.Abstract Large observational databases are often subject to missing data. As such, methods for causal inference must simultaneously handle confounding and missingness; surprisingly little work has been done at this intersection. Motivated by this, we propose an efficient and robust estimator of the causal average treatment effect from cohort studies ...
Alexander W. Levis +3 more
wiley +1 more source
Human Mutation, Volume 43, Issue 12, Page 2170-2186, December 2022., 2022 Abstract The standardization of variant curation criteria is essential for accurate interpretation of genetic results and clinical care of patients. The variant curation guidelines developed by the American College of Medical Genetics and Genomics (ACMG) and the Association for Molecular Pathology (AMP) in 2015 are widely used but are not gene specific.
Kathryn P. Burdon +14 more
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Hidden Markov models for fault detection in dynamic systems [PDF]
, 1994 Padhraic Smyth
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Probabilistic weighted Dirichlet process mixture with an application to stochastic volatility models
Canadian Journal of Statistics, EarlyView.Abstract In this article, we propose a flexible Bayesian modelling framework and investigate the probabilistic weighted Dirichlet process mixture (pWDPM). The construction and properties of a probabilistic weight function are illustrated. The advantage of the pWDPM under the log‐squared transformed stochastic volatility (SV) model is demonstrated.
Peng Sun, Inyoung Kim, Ki‐Ahm Lee
wiley +1 more source