monte-methods: Methods for "'monte'" Object Construction in Package...
In sampSurf: Sampling Surface Simulation for Areal Sampling Methods

Description Methods

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,
      ... )