Usage
anm.mc.bvn(start = c(-4, -4), mu = c(0, 0), sigma = matrix(2, 2, data = c(1, 0,
0, 1)), length = 1000, sim = "M", jump.kernel = 0.2, xlim = c(-4, 4),
ylim = c(-4, 4), interval = 0.01, show.leg = TRUE, cex.leg = 1, ...)
anm.mc.norm(start = -4, mu = 0, sigma = 1, length = 2000, sim = "M",
jump.kernel = 0.2, xlim = c(-4, 4), ylim = c(0, 0.4), interval = 0.01,
show.leg = TRUE,...)
anm.mc.bvn.tck()
Arguments
start
A two element vector specifying the starting coordinates.
mu
A two element vector specifying the mean vector for the proposal distribution.
sigma
A 2 x 2 matrix specifying the variance covariance matrix for the proposal dsitribution.
length
The length of the MCMC chain.
sim
Simulation method used. Must be one of "G" idicating Gibbs sampling, "M" indicating the Metropolis algorithm, or "MH" indicating the Metropolis-Hastings algorithm (Gibbs sampling is not implemented for anm.mc.
jump.kernel
A number > 0 that will serve as a (squared) multiplier for the proposal variance covariance. The result of this multiplication will be used as the variance covariance matrix for the jumping distribution.
xlim
A two element vector describing the upper and lower limits of the x-axis.
ylim
A two element vector describing the upper and lower limits of the y-axis.
interval
Animation interval
show.leg
Logical. Indicating whether or not the chain length should be shown.
cex.leg
Character expansion for legend.
...
Additional arguments from plot.