The following methods for generic function
monte
will construct valid objects of class
"monte
". Please see the ‘“monte”:
When is n Sufficiently Large?’ vignette for more details and
examples.
Please note that each constructor has the same argument list, so it is only stated once below for the first constructor. The signature argument in each case specifies the population from which samples should be drawn.
signature(object = "montePop")
This constructor method is only for use with objects of class
"montePop
". Ultimately, this constructor is
called by all the others.
usage...
monte(object, zeroTruncate = TRUE, n = object@n, mcSamples = 100, type = c('both', 'normalTheory', 'bootstrap'), R = 100, alpha = 0.05, description = 'Monte Carlo Object', replace = TRUE, startSeed = NA, runQuiet = TRUE, ... )
object
: An object of class
"montePop
".
zeroTruncate
: TRUE
: truncate the zero values
from the population; FALSE
: leave it as is.
n
: A vector of sample sizes that will be used to
draw mcSamples
Monte Carlo samples from the population.
mcSamples
: A scalar specifying the number of Monte
Carlo samples to draw from the population of sizes n
.
type
: The type of confidence intervals to
calculate: normal theory, bootstrap, or both.
R
: A scalar specifying the number of bootstrap
sample replicates to draw.
alpha
: The two-tailed alpha level for confidence
interval calculation. I.e., for the 95% confidence level, specify
alpha=0.05
.
replace
: TRUE
: sample with replacement;
FALSE
: sample without replacement. Note that this only
affects how each of the individual mcSamples
samples are
drawn from the population; specifically, note that bootstrapping
is always with replacement from these individual
mcSamples
samples by definition.
description
: A description of the object as a
character string.
startSeed
: A scalar specifying a random number seed
for the Monte Carlo draws. See initRandomSeed
for
details.
runQuiet
: TRUE
: no feedback; FALSE
:
feedback if available.
... : Other arguments to be passed along to
montePop
, monteNTSample
and
monteBSSample
.
signature(object = "numeric")
This constructor method is only for use with objects of class
"numeric
"; i.e., a numeric vector.
usage...
monte(object, zeroTruncate = TRUE, n = c(10), mcSamples = 100, type = c('both', 'normalTheory', 'bootstrap'), R = 100, alpha = 0.05, description = 'Monte Carlo Object', replace = TRUE, startSeed = NA, runQuiet = TRUE, ... )
object
: An object of class
"numeric
". This should be a numeric vector
of appropriate length for the population.
signature(object = "sampSurf")
This constructor method is only for use with objects of class
"sampSurf
". The population will be extracted
from the cell values in the object.
usage...
monte(object, zeroTruncate = TRUE, n = c(10), mcSamples = 100, type = c('both', 'normalTheory', 'bootstrap'), R = 100, alpha = 0.05, description = 'Monte Carlo Object', replace = TRUE, startSeed = NA, runQuiet = TRUE, ... )
object
: An object of class
"sampSurf
".
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