Description Usage Arguments Details Value Author(s) See Also Examples
Generates a parametric bootstrap for the median of scaled differences from each point in a data set to all other points..
1 2 3 4 5 6 7 8 9 10 
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. 
bootMSD
calculates a parametric bootstrap simulation (or Monte carlo simulation)
of the results of msd
applied to data. This allows individual casespecific
quantiles and pvalues 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 pvalues are estimated
directly from the bootstrap replicates. Quantiles use quantile
. pvalues
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.
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.
pvalspvalues 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 by bootMSD
. Set to NA
if keep == FALSE
.
Summary, print and plot methods are provided for the class; see bootMSDclass
.
S. L. R. Ellison s.ellison@lgc.co.uk
msd
, bootMSDclass
, print.bootMSD
,
plot.bootMSD
, summary.bootMSD
.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21  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 pvalues.
# To correct for multiple comparisons, apply
# a suitable pvalue adjustment:
summary(boot.Pb, p.adjust="holm")
## End(Not run)

Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.