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

## Documentation for package ‘codadiags’ version 1.0

- DESCRIPTION file.

## 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