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Results tagged with posterior
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user 116522
In Bayesian statistics, the term 'posterior' refers to the probability distribution of a parameter conditioned on the observed data.
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Using constrained regression model to get closer to the true posterior when doing Approximat...
To get closer to the true posterior I'm using multiple linear regression model as proposed by Beaumont et al 2002. … In that particular context (getting closer to the true posterior), the explicative variables are the SS and the response variables are the paramters of M1 (i.e., $\theta$). …
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Parameter values fall outside the prior range after post-hoc adjustments in the context of A...
I'm doing simple rejection sampling within the Approximate Bayesian Computation framework, and I use regression adjustments (i.e., non-parametric multiple linear regression) to get closer to the true posterior …
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Estimating the posterior predictive distribution post regression adjustment when doing Appro...
I'm currently correcting the parameter values of the posterior distribution estimated with Approximate Bayesian Computation. … From that corrected posterior, I want to estimate the posterior predictive distribution, but I'm worried about how to draw the parameter values from the corrected posterior? …
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Using maximum Likelihood regression to get closer to the true posterior when doing Approxima...
Post-hoc adjustments are used to get closer to the true posterior distribution when doing Approximate Bayesian Computation. … I don't know exactly what to think about that, and the maximum Likelihood framework is good at getting closer to the true posterior distribution. …
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