Results 171 to 180 of about 101,818 (290)

A cautious user's guide in applying HMMs to physical systems. [PDF]

J Chem Phys
Schweiger M, Saurabh A, Pressé S.
europepmc   +1 more source

Machine Learning‐Based Risk‐Adjusted CUSUM Control Chart for Monitoring Readmission Rate Following PTBD Catheter Placement

Quality and Reliability Engineering International, Volume 42, Issue 3, Page 933-949, April 2026.
ABSTRACT Percutaneous transhepatic biliary drainage (PTBD) catheter placement is known to have a high readmission rate. This work focuses on monitoring the change in readmission rate after a new clinical paradigm for post‐procedural care is implemented for the PTBD procedures.
Muhammed Aljifri, Yanjun Qian, Kunal Patel   +2 more
wiley   +1 more source

Giant anteaters on the move: native habitat selection and behavioral responses to land use change. [PDF]

Mov Ecol
Meiga AYY, Desbiez ALJ, Dornas RAP, Attias N, Giroux A, Valle D.   +5 more
europepmc   +1 more source

Testing Hypotheses of Covariate Effects on Topics of Discourse

Statistical Analysis and Data Mining: An ASA Data Science Journal, Volume 19, Issue 2, April 2026.
ABSTRACT We introduce an approach to topic modeling with document‐level covariates that remains tractable in the face of large text corpora. This is achieved by de‐emphasizing the role of parameter estimation in an underlying probabilistic model, assuming instead that the data come from a fixed but unknown distribution whose statistical functionals are
Gabriel Phelan, David A. Campbell
wiley   +1 more source

Infinite hidden Markov models can dissect the complexities of learning. [PDF]

Nat Neurosci
Bruijns SA, International Brain Laboratory, Bougrova K, Laranjeira IC, Lau PYP, Meijer GT, Miska NJ, Noel JP, Pan-Vazquez A, Roth N, Socha KZ, Urai AE, Dayan P.   +12 more
europepmc   +1 more source

Financial Time Series Uncertainty: A Review of Probabilistic AI Applications

Journal of Economic Surveys, Volume 40, Issue 2, Page 915-953, April 2026.
ABSTRACT Probabilistic machine learning models offer a distinct advantage over traditional deterministic approaches by quantifying both epistemic uncertainty (stemming from limited data or model knowledge) and aleatoric uncertainty (due to inherent randomness in the data), along with full distributional forecasts.
Sivert Eggen, Tord Johan Espe, Kristoffer Grude, Morten Risstad, Rickard Sandberg   +4 more
wiley   +1 more source

Latent classification of time-dependent transition rates in longitudinal binary outcome data. [PDF]

Stat Methods Med Res
Chang J, Chan W.
europepmc   +1 more source

The Monetary Policy–Commodities Nexus: A Survey

Journal of Economic Surveys, Volume 40, Issue 2, Page 1050-1082, April 2026.
ABSTRACT This survey synthesizes evidence on the bidirectional links between commodity markets and monetary policy. On the commodities‐to‐policy side, we review how shocks to energy, food, and metals pass through to inflation, inflation expectations, economic activity, and financial stability in state‐dependent ways that vary by shock type, exposure ...
Martin T. Bohl, Niklas Humann, Pierre L. Siklos   +2 more
wiley   +1 more source

Stochastic Modelling of Daily Precipitation in Semi‐Arid Regions Using Markov Chains and Parametric Distributions

International Journal of Climatology, Volume 46, Issue 4, 30 March 2026.
This study applies stochastic rainfall models combining Markov Chains with gamma and mixed exponential distributions to a semi‐arid climate in Northeast Brazil. Model structures were evaluated using Bayesian Information Criterion (BIC), with maximum likelihood (MLM) for parameter estimation and cumulative distribution functions (CDFs) for validation ...
Gabriel Magno Cavalcante Calado, Mayke Feitosa Progênio, José Adalberto da Silva Filho, Ialy Rayane de Aguiar Costa, Severino Martins Neto, Artur Paiva Coutinho   +5 more
wiley   +1 more source

Neural parameter calibration for dengue outbreak forecasting. [PDF]

PLoS One
Pham HV, Nguyen KTD, Velavan TP, Tran KD.   +3 more
europepmc   +1 more source