Usage
PLUE(model=NULL, factors, N, LL, start, res.names=NULL, method = c("internal", "mcmc"),
opts = list(), nboot=0, repetitions=1, cl=NULL)
## S3 method for class 'PLUE':
print(x, ...)
## S3 method for class 'PLUE':
plot(x, ...)Arguments
model
The function to be run, representing the model or simulation.
factors
The names of the input variables (used for naming the 'data' data.frame and in plotting)
Either a vector of strings or a single number representing the number of factors
N
The number of samples to be generated by the Metropolis algorithm.
LL
The POSITIVE Likelihood function to be used by the Metropolis algorithm. It must accept
an array with length equal to the number of factors.
start
The initial point to be evaluated. Must have the same length as the number of factors.
res.names
Optional: what are the names of the model results? (Used mainly for plotting)
method
May be either "internal", which runs a naive and inneficient algorithm provided for test
and didatic purposes, or "mcmc", which will run the metrop function from the mcmc package.
opts
Further options to be passed to the Metropolis function. See the help on mcmc::metrop.
nboot
Number of bootstrap replicates for calculating the PRCC.
repetitions
The number of model repetitions to be run for a single data point. See the vignette on
stochastic models for details
cl
Cluster generated with the ``parallel'' library. May be of any type supported.
If a cluster is provided, the model will be run in parallel or distributed across
the cluster via clusterApply. No load balancing is provided, so the model results are
re