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adaptive metropolis–hastings algorithm  (Millar Inc)

 
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    Millar Inc adaptive metropolis–hastings algorithm
    Adaptive Metropolis–Hastings Algorithm, supplied by Millar Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/adaptive+metropolis%E2%80%93hastings+algorithm/adaptive+metropolis+hastings+algorithm/10__1002_slash_jwmg__672-90-9-13
    Average 90 stars, based on 1 article reviews
    adaptive metropolis–hastings algorithm - by Bioz Stars, 2026-10
    90/100 stars

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    Article Title: Monitoring and modeling of population dynamics for the harvest management of scaly-naped pigeons in Puerto Rico
    Article Snippet: The scaly-naped pigeon (Patagioenas squamosa) is threatened by hunting in the Caribbean.. At present, the pigeon is abundant in Puerto Rico, but overharvesting is a major concern; therefore, the development of a sustainable harvest strategy is a management priority.. The management objective of the harvest strategy is to maximize hunting opportunity while keeping the population above an abundance threshold (NT) of 260,000 pigeons.



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    Epidemiological parameter estimates, ranges, and their sources. Prior distributions, posterior means and corresponding confidence intervals, and the Geweke index are provided for estimated epidemiological parameters (shaded cells) using the delayed <t> rejection adaptive Metropolis-Hastings (DRAM) algorithm </t> in a Markov-Chain Monte-Carlo (MCMC) framework.
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    Epidemiological parameter estimates, ranges, and their sources. Prior distributions, posterior means and corresponding confidence intervals, and the Geweke index are provided for estimated epidemiological parameters (shaded cells) using the delayed <t> rejection adaptive Metropolis-Hastings (DRAM) algorithm </t> in a Markov-Chain Monte-Carlo (MCMC) framework.
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    Epidemiological parameter estimates, ranges, and their sources. Prior distributions, posterior means and corresponding confidence intervals, and the Geweke index are provided for estimated epidemiological parameters (shaded cells) using the delayed rejection adaptive Metropolis-Hastings (DRAM) algorithm in a Markov-Chain Monte-Carlo (MCMC) framework.

    Journal: Epidemics

    Article Title: Synthesizing data and models for the spread of MERS-CoV, 2013: Key role of index cases and hospital transmission

    doi: 10.1016/j.epidem.2014.09.011

    Figure Lengend Snippet: Epidemiological parameter estimates, ranges, and their sources. Prior distributions, posterior means and corresponding confidence intervals, and the Geweke index are provided for estimated epidemiological parameters (shaded cells) using the delayed rejection adaptive Metropolis-Hastings (DRAM) algorithm in a Markov-Chain Monte-Carlo (MCMC) framework.

    Article Snippet: We used a delayed rejection adaptive Metropolis-Hastings (DRAM) algorithm in a Markov-Chain Monte-Carlo (MCMC) framework which has been previously described in ref. ( ) (Matlab package available from: http://helios.fmi.fi/∼lainema/mcmc/ ).

    Techniques: Transmission Assay