gev.impute: Given the output of the MCMC, return a number of samples for...
In NorskRegnesentral/SpatGEVBMA: Hierarchical spatial generalized extreme value (GEV) modeling with Bayesian Model Averaging (BMA)
gev.impute R Documentation
Given the output of the MCMC, return a number of samples for a new site.
Description
This takes the object returned from spatial.gev.bma and new
information for a given site and returns a large sample of values
from the posterior predictive distribution for that site.
Usage
gev.impute(R, X.drop, S.drop, burn = NULL, n.each = NULL)
Arguments
R
This is the object returned from spatial.gev.bma
X.drop
This is the vector of covariates for the site that has been left out.
S.drop
This is the 2 dimensional vector of locations for this site
burn
Optional number of repetitions to drop from R as burn in. Defaults
to 10 percent.
n.each
Optional number of samples from each repetition under
consideration. Defaults to a number such that around 1 million
samples are returned.
Value
Returns a large number of sample from the posterior predictive
distribution.
Author(s)
Alex Lenkoski <alex@nr.no>
NorskRegnesentral/SpatGEVBMA documentation built on July 22, 2023, 9:59 a.m.
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| gev.impute | R Documentation |
Given the output of the MCMC, return a number of samples for a new site.
Description
This takes the object returned from spatial.gev.bma and new information for a given site and returns a large sample of values from the posterior predictive distribution for that site.
Usage
gev.impute(R, X.drop, S.drop, burn = NULL, n.each = NULL)
Arguments
R |
This is the object returned from spatial.gev.bma |
X.drop |
This is the vector of covariates for the site that has been left out. |
S.drop |
This is the 2 dimensional vector of locations for this site |
burn |
Optional number of repetitions to drop from R as burn in. Defaults to 10 percent. |
n.each |
Optional number of samples from each repetition under consideration. Defaults to a number such that around 1 million samples are returned. |
Value
Returns a large number of sample from the posterior predictive distribution.
Author(s)
Alex Lenkoski <alex@nr.no>
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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