Generates a parametric bootstrap for the median of scaled differences from each point in a data set to all other points..
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An R object. For the default method, a vector of observations. For the
Either a function returning an estimate of scale for
Scalar number of bootstrap replicates.
Vector of probabilities at which to calculate upper quantiles. Passed to
Character value describing the simulation method.
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 case-specific
quantiles and p-values to be estimated that allow for different standard errors
(or standard uncertainties)
The sampling method is currently either sampling from
rnorm or by latin hypercube sampling
Individual upper quantiles for probabilities
probs and p-values are estimated
directly from the bootstrap replicates. Quantiles use
are estimated from the proportion of replicates that exceed the observed MSD calculated by
msd. Note that 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
labelscharacter vector of labels, by default taken from
probsvextor of probabilities supplied and used for quantiles
critical.valuesmatrix of quantiles. Each row corresponds to a probability
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
BNumber of bootstrap replicates used.
methodThe sampling method used by the parametric bootstrap.
keep == TRUE, the individual bootstrap replicates
bootMSD. Set to
keep == FALSE.
Summary, print and plot methods are provided for the class; see
S. L. R. Ellison firstname.lastname@example.org
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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)
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