estimateWhiteningMatrix {BSL}  R Documentation 
Estimate the Whitening matrix to be used in the “wBSL” method of Priddle et al. (2021)
Description
This function estimates the Whitening matrix to be used in BSL with Warton's shrinkage and Whitening (“wBSL” method of Priddle et al. (2021)). The Whitening transformation and decorrelation methods are detailed in Kessy et al. (2018).
Usage
estimateWhiteningMatrix(
n,
model,
method = c("PCA", "ZCA", "Cholesky", "ZCAcor", "PCAcor"),
thetaPoint = NULL,
parallel = FALSE,
parallelArgs = NULL
)
Arguments
n 
The number of model simulations to estimate the Whitening matrix. 
model 
A “MODEL” object generated with function

method 
The type of Whitening method to be used. The default is “PCA”. 
thetaPoint 
A point estimate of the parameter value with nonnegligible posterior support. 
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

Value
The estimated Whitening matrix.
References
Kessy A, Lewin A, Strimmer K (2018).
“Optimal Whitening and Decorrelation.”
The American Statistician, 72(4), 309–314.
doi: 10.1080/00031305.2016.1277159.
Priddle JW, Sisson SA, Frazier DT, Turner I, Drovandi C (2021).
“Efficient Bayesian Synthetic Likelihood with Whitening Transformations.”
Journal of Computational and Graphical Statistics (In Press).
https://arxiv.org/abs/1909.04857.
Examples
## Not run:
data(ma2)
model < newModel(fnSim = ma2_sim, fnSum = ma2_sum, simArgs = ma2$sim_args, theta0 = ma2$start)
W < estimateWhiteningMatrix(20000, model, method = "PCA", thetaPoint = c(0.6, 0.2))
## End(Not run)