plot.mlmc.test: Plot an 'mlmc.test' object

In louisaslett/mlmc: Multi-Level Monte Carlo

Plot an mlmc.test object

Description

Produces diagnostic plots on the result of an mlmc.test function call.

Usage

## S3 method for class 'mlmc.test'
plot(x, which = "all", cols = NA, ...)

Arguments

x	an mlmc.test object as produced by a call to the mlmc.test function.
which	a vector of strings specifying which plots to produce, or "all" to do all diagnostic plots The options are: "var" = \log_2 of variance against level; "mean" = \log_2 of the absolute value of the mean against level; "consis" = consistency against level; "kurt" = kurtosis against level; "Nl" = \log_2 of number of samples against level; "cost" = \log_{10} of cost against \log_{10} of epsilon (accuracy).
cols	the number of columns across to plot to override the default value.
...	additional arguments which are passed on to plotting functions.

Details

Most of the plots produced are relatively self-explanatory. However, the consistency and kurtosis plots in particular may require some background. It is highly recommended to refer to Section 3.3 of Giles (2015), where the rationale for these diagnostic plots is addressed in full detail.

Value

No return value, called for side effects.

Author(s)

Louis Aslett <[e-mail]>

References

Giles, M.B. (2015) 'Multilevel Monte Carlo methods', Acta Numerica, 24, pp. 259–328. Available at: \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1017/S096249291500001X")}.

Examples

tst <- mlmc.test(opre_l, N = 2000000,
                 L = 5, N0 = 1000,
                 eps.v = c(0.005, 0.01, 0.02, 0.05, 0.1),
                 Lmin = 2, Lmax = 6,
                 option = 1)
tst
plot(tst)

louisaslett/mlmc documentation built on Sept. 3, 2024, 10:36 p.m.