trim {deepgp} | R Documentation |
Trim/Thin MCMC iterations
Description
Acts on a gp
, gpvec
, dgp2
, dgp2vec
,
dgp3vec
, or dgp3
object.
Removes the specified number of MCMC iterations (starting at the first
iteration). After these samples are removed, the remaining samples are
optionally thinned.
Usage
trim(object, burn, thin)
## S3 method for class 'gp'
trim(object, burn, thin = 1)
## S3 method for class 'gpvec'
trim(object, burn, thin = 1)
## S3 method for class 'dgp2'
trim(object, burn, thin = 1)
## S3 method for class 'dgp2vec'
trim(object, burn, thin = 1)
## S3 method for class 'dgp3'
trim(object, burn, thin = 1)
## S3 method for class 'dgp3vec'
trim(object, burn, thin = 1)
Arguments
object |
object from |
burn |
integer specifying number of iterations to cut off as burn-in |
thin |
integer specifying amount of thinning ( |
Details
The resulting object will have nmcmc
equal to the previous
nmcmc
minus burn
divided by thin
. It is
recommended to start an MCMC fit then investigate trace plots to assess
burn-in. Once burn-in has been achieved, use this function to remove
the starting iterations. Thinning reduces the size of the resulting
object while accounting for the high correlation between consecutive
iterations.
Value
object of the same class with the selected iterations removed
Examples
# See "fit_one_layer", "fit_two_layer", or "fit_three_layer"
# for an example