MODELclass {BSL}  R Documentation 
S4 class “MODEL”
Description
The S4 class contains the simulation and summary statistics
function and other necessary arguments for a model to run in the main
bsl
function.
newModel
is the constructor function for a MODEL
object.
simulation
runs a number of simulations and computes the
correponding summary statistics with the provided model.
summStat
computes the summary statistics with the given data and model object.
The summary statistics function and relevant arguments are obtained from the model.
Usage
newModel(
fnSim,
fnSimVec,
fnSum,
fnLogPrior,
simArgs,
sumArgs,
theta0,
thetaNames,
test = TRUE,
verbose = TRUE
)
## S4 method for signature 'MODEL'
simulation(
model,
n = 1,
theta = model@theta0,
summStat = TRUE,
parallel = FALSE,
parallelArgs = NULL,
seed = NULL
)
## S4 method for signature 'ANY,MODEL'
summStat(x, model)
Arguments
fnSim 
A function that simulates data for a given parameter
value. The first argument should be the parameters. Other necessary
arguments (optional) can be specified with 
fnSimVec 
A vectorised function that simulates a number of
datasets simultaneously for a given parameter value. The first two
arguments should be the number of simulations to run and parameters,
respectively. Other necessary arguments (optional) can be specified with

fnSum 
A function for computing summary statistics of data. The
first argument should be the observed or simulated dataset. Other necessary
arguments (optional) can be specified with 
fnLogPrior 
A function that computes the log of prior density for a parameter. If this is missing, the prior by default is an improper flat prior over the real line for each parameter. The function must have a single input: a vector of parameter values. 
simArgs 
A list of additional arguments to pass into the simulation
function. Only use when the input 
sumArgs 
A list of additional arguments to pass into the summary
statistics function. Only use when the input 
theta0 
Initial guess of the parameter value. 
thetaNames 
A string vector of parameter names, which must have the same length as the parameter vector. 
test 
Logical, whether a short simulation test will be ran upon initialisation. 
verbose 
Logical, whether to print verbose messages when initialising a “MODEL” object. 
model 
A “MODEL” class object. 
n 
The number of simulations to run. 
theta 
The parameter value. 
summStat 
Logical indicator whether the correpsonding summary statistics
should be returned or not. The default is 
parallel 
A logical value indicating whether parallel computing should
be used for simulation and summary statistic evaluation. The default is

parallelArgs 
A list of additional arguments to pass into the

seed 
A seed number to pass to the 
x 
The data to pass to the summary statistics function. 
Value
A list of simulation results using the given parameter. x
contains the raw simulated datasets. ssx
contains the summary
statistics.
A vector of the summary statistics.
Slots
fnSim
A function that simulates data for a given parameter value. The first argument should be the parameters. Other necessary arguments (optional) can be specified with
simArgs
.fnSimVec
A vectorised function that simulates a number of datasets simultaneously for a given parameter value. If this is not
NULL
, vectorised simulation function will be used instead offnSim
. The first two arguments should be the number of simulations to run and parameters, respectively. Other necessary arguments (optional) can be specified withsimArgs
. The output must be a list of each simulation result.fnSum
A function for computing summary statistics of data. The first argument should be the observed or simulated dataset. Other necessary arguments (optional) can be specified with
sumArgs
. The users should code this function carefully so the output have fixed length and never contain anyInf
value.fnLogPrior
A function that computes the log of prior density for a parameter. The default is
NULL
, which uses an improper flat prior over the real line for each parameter. The function must have a single input: a vector of parameter values.simArgs
A list of additional arguments to pass into the simulation function. Only use when the input
fnSim
orfnSimVec
requires additional arguments. The default isNULL
.sumArgs
A list of additional arguments to pass into the summary statistics function. Only use when the input
fnSum
requires additional arguments. The default isNULL
.theta0
Initial guess of the parameter value, which is used as the starting value for MCMC.
thetaNames
Expression, parameter names.
ns
The number of summary statistics of a single observation. Note this will be generated automatically, thus is not required for initialisation.
test
Logical, whether a short simulation test will be ran upon initialisation.
verbose
Logical, whether to print verbose messages when initialising a “MODEL” object.
Examples
# set up the model for the ma2 example
data(ma2)
m < newModel(fnSim = ma2_sim, fnSum = ma2_sum, simArgs = ma2$sim_args,
theta0 = ma2$start, fnLogPrior = ma2_prior, verbose = FALSE)
validObject(m)
# benchmark the serial and vectorised simulation function (require the rbenchmark package)
m1 < newModel(fnSim = ma2_sim, fnSum = ma2_sum, simArgs = ma2$sim_args,
theta0 = ma2$start, fnLogPrior = ma2_prior)
m2 < newModel(fnSimVec = ma2_sim_vec, fnSum = ma2_sum, simArgs = ma2$sim_args,
theta0 = ma2$start, fnLogPrior = ma2_prior)
require("rbenchmark")
## Not run:
benchmark(serial = simulation(m1, n = 1000, theta = c(0.6, 0.2)),
vectorised = simulation(m2, n = 1000, theta = c(0.6, 0.2)))
## End(Not run)