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Function computes the monte-carlo mean of a function by varying the parameter inputs to the function
mc_mean(ofv_fcn, poped.db, bpopdescr = poped.db$parameters$bpop,
ddescr = poped.db$parameters$d, doccdescr = poped.db$parameters$d,
user_distribution_pointer = poped.db$model$user_distribution_pointer,
ED_samp_size = poped.db$settings$ED_samp_size,
bLHS = poped.db$settings$bLHS, ...)
A function with poped.db as the first input
A PopED database.
Matrix defining the fixed effects, per row (row number = parameter_number) we should have:
column 1 the type of the distribution for E-family designs (0 = Fixed, 1 = Normal, 2 = Uniform, 3 = User Defined Distribution, 4 = lognormal and 5 = truncated normal)
column 2 defines the mean.
column 3 defines the variance of the distribution (or length of uniform distribution).
Matrix defining the diagnonals of the IIV (same logic as for
the bpopdescr
).
Matrix defining the IOV. per row (row number = parameter_number) we should have:
column 1 the type of the distribution for E-family designs (0 = Fixed, 1 = Normal, 2 = Uniform, 3 = User Defined Distribution, 4 = lognormal and 5 = truncated normal)
column 2 defines the mean of the variance.
column 3 defines the variance of the distribution (or length of uniform distribution).
Function name for user defined distributions for E-family designs
Sample size for E-family sampling
How to sample from distributions in E-family calculations. 0=Random Sampling, 1=LatinHyperCube --
Other arguments passed to the function.
The mean of the function evaluated at different parameter values.