Bayes.fit-class

S4 class for the Bayesian estimation results

Inference on stochastic differential models Ornstein-Uhlenbeck or
Cox-Ingersoll-Ross, with one or two random effects in the drift function.

Charlotte Dion

mixedsde

Estimation Methods for Stochastic Differential Mixed Effects
Models

Bayes.fit-class function

<dl class="dl-horizontal">
<dt><code>sigma2</code></dt><dd>vector of posterior samples for \(\sigma^2\)</dd></dl><dt><code>mu</code></dt><dd>matrix of posterior samples for \(\mu\)</dd><dt><code>omega</code></dt><dd>matrix of posterior samples for \(\omega\)</dd><dt><code>alpha</code></dt><dd>matrix of posterior samples for \(\alpha\)</dd><dt><code>beta</code></dt><dd>matrix of posterior samples for \(\beta\)</dd><dt><code>random</code></dt><dd>1, 2 or c(1,2)</dd><dt><code>burnIn</code></dt><dd>proposal for the burn-in phase</dd><dt><code>thinning</code></dt><dd>proposal for the thinning rate</dd><dt><code>model</code></dt><dd>'OU' or 'CIR'</dd><dt><code>prior</code></dt><dd>list of prior values, input variable or calculated by the first 10% of series</dd><dt><code>times</code></dt><dd>vector of observation times, storage of input variable</dd><dt><code>X</code></dt><dd>matrix of observations, storage of input variable</dd><dt><code>ind.4.prior</code></dt><dd>indices of series used for the prior parameter calculation, if prior knowledge is availabe it is set to M+1</dd>

Bayes.fit-class: S4 class for the Bayesian estimation results

Description

Arguments

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