Mathematical derivations for the Monte Carlo sampling routine used and analyses of Monte Carlo error for approximating the likelihood of a domain
Detailed tables of parameters used for simulations and tables and figures of estimations of specific...
Coefficients and error distributions for each vital rate used in the integral projection model
Descriptions of the derivation of likelihood and restricted likelihood functions for an ARMA(p,q) pr...
Mathematical derivations for the Monte Carlo sampling routine used and analyses of Monte Carlo error...
A description of the Gibbs sampler, which uses Markov chain Monte Carlo (MCMC) methods
Markov-chain Monte Carlo algorithms, together with prior parameter values, marginal posteriors, a di...
Description of Markov chain Monte Carlo (MCMC) methods used to simulate from the full conditional di...
Supplemental methods for Markov Chain Monte Carlo and additional results for ontogenetic changes in ...
Calculation of standard errors, superpopulation estimates, and confidence intervals for Alley North ...
Prior distributions, conditional relationships and distribution theory needed for algorithm developm...
28 pages, 1 article*Statistical Inference and Monte Carlo Algorithms* (Casella, George) 28 page
Contains fulltext : 161282.pdf (preprint version ) (Open Access
Contains fulltext : 35870.pdf (author's version ) (Open Access)Electronic Article ...
As our multi-stage Monte Carlo method requires finding the maxima of correlated random variables gen...
A box-and-whisker plot of point estimates of error rate and figures showing results of simulations
Detailed tables of parameters used for simulations and tables and figures of estimations of specific...
Coefficients and error distributions for each vital rate used in the integral projection model
Descriptions of the derivation of likelihood and restricted likelihood functions for an ARMA(p,q) pr...
Mathematical derivations for the Monte Carlo sampling routine used and analyses of Monte Carlo error...
A description of the Gibbs sampler, which uses Markov chain Monte Carlo (MCMC) methods
Markov-chain Monte Carlo algorithms, together with prior parameter values, marginal posteriors, a di...
Description of Markov chain Monte Carlo (MCMC) methods used to simulate from the full conditional di...
Supplemental methods for Markov Chain Monte Carlo and additional results for ontogenetic changes in ...
Calculation of standard errors, superpopulation estimates, and confidence intervals for Alley North ...
Prior distributions, conditional relationships and distribution theory needed for algorithm developm...
28 pages, 1 article*Statistical Inference and Monte Carlo Algorithms* (Casella, George) 28 page
Contains fulltext : 161282.pdf (preprint version ) (Open Access
Contains fulltext : 35870.pdf (author's version ) (Open Access)Electronic Article ...
As our multi-stage Monte Carlo method requires finding the maxima of correlated random variables gen...
A box-and-whisker plot of point estimates of error rate and figures showing results of simulations
Detailed tables of parameters used for simulations and tables and figures of estimations of specific...
Coefficients and error distributions for each vital rate used in the integral projection model
Descriptions of the derivation of likelihood and restricted likelihood functions for an ARMA(p,q) pr...
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