<p>Probability densities for each of the parameters described in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.0030193#pbio-0030193-g001" target="_blank">Figure 1</a> are shown, as follows: (A) θ<sub>1</sub>; (B) θ<sub>2</sub>; (C) θ<sub>A</sub>; (D) <i>t</i> (i.e., t/u); (E) t shown on a scale of years over the range corresponding to a maximum <i>t</i> value of 0.2; (F) <i>s;</i> (G) <i>m</i><sub>1</sub>; and (H) <i>m</i><sub>2</sub>. The analysis in which a high upper limit on the prior distribution for <i>t</i> was used is identified as “high <i>t<sub>upper</sub></i>,” while those analyses with a smaller upper limit on the prior distribution of <i>t</i> are identified as “low <i>t<sub>upper</sub></i>.” Each cu...
<p>Distributions are for (A) instantaneous rate of population increase (), (B) detection rate () and...
Abstract: We consider nonparametric Bayesian estimation of a probabil-ity density p based on a rando...
貝氏因子(Bayes factor) 是貝氏統計方法中對於推論假設檢定(hypothesis testing)所用的一個 統計量。它的定義可以表成兩個資料的邊際機率(marginal probabil...
<p>Marginal posterior distributions with 1000 samples from each posterior mode are shown for <i>α</i...
Each subplot shows the histogram of the samples from the approximate parameter posterior. The x-axis...
<p>Parameter estimates are consistent with theoretical expectations (e.g. older and larger populatio...
<p>Posterior densities for age estimates for the calibrated nodes based on the full analysis (light ...
<p>After data are obtained the posterior distributions are much more tightly-constrained, and are pi...
<p>A critical step for any Bayesian analysis is the examination of the influence of prior densities ...
<p>Each panel shows the marginal posterior distributions over a single parameter for each subject an...
<p>Approximate posterior distributions for: (A) Year of introduction; (B) Relationship between repro...
grantor: University of TorontoA fully Bayesian method is developed for modelling the distr...
<p>The histograms (along the main diagonal from top to bottom) show the marginal posterior distribut...
<p>The input parameters for the simulations were as follows: (A) θ<sub>1</sub> = 10; (B) θ<sub>2</su...
<p>Running the sampler with no data so that the posterior probabilities are determined by the prior ...
<p>Distributions are for (A) instantaneous rate of population increase (), (B) detection rate () and...
Abstract: We consider nonparametric Bayesian estimation of a probabil-ity density p based on a rando...
貝氏因子(Bayes factor) 是貝氏統計方法中對於推論假設檢定(hypothesis testing)所用的一個 統計量。它的定義可以表成兩個資料的邊際機率(marginal probabil...
<p>Marginal posterior distributions with 1000 samples from each posterior mode are shown for <i>α</i...
Each subplot shows the histogram of the samples from the approximate parameter posterior. The x-axis...
<p>Parameter estimates are consistent with theoretical expectations (e.g. older and larger populatio...
<p>Posterior densities for age estimates for the calibrated nodes based on the full analysis (light ...
<p>After data are obtained the posterior distributions are much more tightly-constrained, and are pi...
<p>A critical step for any Bayesian analysis is the examination of the influence of prior densities ...
<p>Each panel shows the marginal posterior distributions over a single parameter for each subject an...
<p>Approximate posterior distributions for: (A) Year of introduction; (B) Relationship between repro...
grantor: University of TorontoA fully Bayesian method is developed for modelling the distr...
<p>The histograms (along the main diagonal from top to bottom) show the marginal posterior distribut...
<p>The input parameters for the simulations were as follows: (A) θ<sub>1</sub> = 10; (B) θ<sub>2</su...
<p>Running the sampler with no data so that the posterior probabilities are determined by the prior ...
<p>Distributions are for (A) instantaneous rate of population increase (), (B) detection rate () and...
Abstract: We consider nonparametric Bayesian estimation of a probabil-ity density p based on a rando...
貝氏因子(Bayes factor) 是貝氏統計方法中對於推論假設檢定(hypothesis testing)所用的一個 統計量。它的定義可以表成兩個資料的邊際機率(marginal probabil...