Bayes.fit-class function

class

S4 class for the Bayesian estimation results

Slots

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