# Markov chain Monte Carlo burn-in based on "bridge" statistics ## Help Pages

 codadiags-package Markov chain Monte Carlo burn-in based on "bridge" statistics. ad.cdf Anderson-Darling cumulative density function, copy from ADGofTest package. add.transient Add a transient to a given mcmc sequence AR1 Generate auto-regressive order 1 sequence autocorr1 Basic auto-correlation estimation of a given sequence bay.cdf Bay cumulative density function, corresponding to -B(t+)/B(t-), where B(t+) (resp. B(t-)) is the maximum (resp.minimum) of B(t)/(t*(1-t)). bridgestat.diag Iterative truncation procedure based on a bridge statistic. brownianbridge Compute the so called (abusively) "Brownian bridge" process. codadiags Markov chain Monte Carlo burn-in based on "bridge" statistics. cvm.cdf Cramer von Mises cumulative density function, import from coda package. ks.cdf Kolmogorov-Smirnov cumulative density function, copy from stats::ks.test. loglikbridge Compute the so called "Log-likelihood bridge" process. maxinv.bay.cdf CDF of max(x,1/x) (=cdf(x)-cdf(1)+cdf(1)-cdf(1/x)) where x is 'Bay' distributed null.lim.cdf Asymptotic CDF for a given statistic null.param.cdf Build the null CDF (cumulative density function) for a given statistic, for arbitrary length and autocorrelation sequence. studentbridge Compute the so called "Student bridge" process. transient.test Perform a stationary test to check for an initial burn-in in a sequence