Phenomenological forecasting of disease incidence using heteroskedastic Gaussian processes: a dengue case study

DOI10.1214/17-AOAS1090zbMath1393.62071arXiv1702.00261OpenAlexW2963562749WikidataQ60204112 ScholiaQ60204112MaRDI QIDQ1647581

Jason Rohr, Daniel Weikel, Leah R. Johnson, Erin Mordecai, Sadie J. Ryan, Robert B. Gramacy, Jeremy Cohen, Anna M. Stewart-Ibarra, Courtney Murdock

Publication date: 26 June 2018

Published in: The Annals of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1702.00261

zbMATH Keywords

Gaussian processepidemiologylatent variabledengue fevergeneralized linear (autoregressive) modelheteroskedastic modeling

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20) Inference from spatial processes (62M30) Applications of statistics to biology and medical sciences; meta analysis (62P10) Medical epidemiology (92C60)

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Uses Software

• R
• S-PLUS
• laGP
• GitHub

Cites Work

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