bootMSD {metRology} | R Documentation |
Parametric bootstrap for median scaled difference
Description
Generates a parametric bootstrap for the median of scaled differences from each point in a data set to all other points..
Usage
bootMSD(x, ...)
## Default S3 method:
bootMSD(x, s = mad, B = 3000, probs = c(0.95, 0.99),
method = c("rnorm", "lhs"), keep = FALSE, labels = names(x), ...)
## S3 method for class 'MSD'
bootMSD(x, B = 3000, probs = c(0.95, 0.99),
method = c("rnorm", "lhs"), keep = FALSE, labels = names(x), ...)
Arguments
x |
An R object. For the default method, a vector of observations. For the |
s |
Either a function returning an estimate of scale for |
B |
Scalar number of bootstrap replicates. |
probs |
Vector of probabilities at which to calculate upper quantiles. Passed to
|
method |
Character value describing the simulation method. |
keep |
If |
labels |
Character vector of labels for individual values. |
... |
Parameters passed to other methods. |
Details
bootMSD
calculates a parametric bootstrap simulation (or Monte carlo simulation)
of the results of msd
applied to data. This allows individual case-specific
quantiles and p-values to be estimated that allow for different standard errors
(or standard uncertainties) s
.
The sampling method is currently either sampling from rnorm
or by latin hypercube sampling
using lhs
.
Individual upper quantiles for probabilities probs
and p-values are estimated
directly from the bootstrap replicates. Quantiles use quantile
. p-values
are estimated from the proportion of replicates that exceed the observed MSD calculated by
msd
. Note that the print
method for the summary
object does
not report zero proportions as identically zero.
Value
An object of class "bootMSD", consisting of a vector of length length(x)
of median
scaled absolute deviations for each observation, with attributes:
msdvector of raw calculated MSD values calculated by
msd
labelscharacter vector of labels, by default taken from
x
probsvextor of probabilities supplied and used for quantiles
critical.valuesmatrix of quantiles. Each row corresponds to a probability in
probs
and each column to an individual data point.pvalsp-values estimated as the observed proportion of simulated values exceeding the MSD value calculated by
msd
.BNumber of bootstrap replicates used.
methodThe sampling method used by the parametric bootstrap.
tIf
keep == TRUE
, the individual bootstrap replicates generated bybootMSD
. Set toNA
ifkeep == FALSE
.
Summary, print and plot methods are provided for the class; see bootMSD-class
.
Author(s)
S. L. R. Ellison s.ellison@lgc.co.uk
See Also
msd
, bootMSD-class
, print.bootMSD
,
plot.bootMSD
, summary.bootMSD
.
Examples
data(Pb)
## Not run:
#Default method:
set.seed(1023)
boot.Pb.default <- bootMSD(Pb$value, Pb$u) # Uses individual standard uncertainties
summary(boot.Pb.default)
#Method for MSD object:
msd.Pb<-msd(Pb$value, Pb$u) # Uses individual standard uncertainties
boot.Pb <- bootMSD(msd.Pb, B=5000)
#Increased replication compared to default
summary(boot.Pb)
# NOTE: The default summary gives individual observation p-values.
# To correct for multiple comparisons, apply
# a suitable p-value adjustment:
summary(boot.Pb, p.adjust="holm")
## End(Not run)