deprecated: Deprecated functions
In inbo/multimput: Using Multiple Imputation to Address Missing Data

generateData

R Documentation

Deprecated functions

Description

These functions will be removed from multimput in the future.

Usage

generateData(
  intercept = 2,
  n.year = 24,
  n.period = 6,
  n.site = 20,
  year.factor = FALSE,
  period.factor = FALSE,
  site.factor = FALSE,
  trend = 0.01,
  sd.rw.year = 0.1,
  amplitude.period = 1,
  mean.phase.period = 0,
  sd.phase.period = 0.2,
  sd.site = 1,
  sd.rw.site = 0.02,
  sd.noise = 0.01,
  size = 2,
  n.run = 10,
  as.list = FALSE,
  details = FALSE
)

missingAtRandom(
  dataset,
  proportion = 0.25,
  count.variable = "Count",
  observed.variable = "Observed"
)

missingCurrentCount(
  dataset,
  proportion = 0.25,
  count.variable = "Count",
  observed.variable = "Observed"
)

missingObserved(
  dataset,
  count.variable = "Count",
  observed.variable = "Observed",
  site.variable = "Site",
  year.variable = "Year",
  period.variable = "Period"
)

missingVolunteer(
  dataset,
  proportion = 0.25,
  count.variable = "Count",
  observed.variable = "Observed",
  year.variable = "Year",
  site.variable = "Site",
  max.count = 100
)

Arguments

`intercept`	The global mean on the log-scale.
`n.year`	The number of years.
`n.period`	The number of periods.
`n.site`	The number of sites.
`year.factor`	Convert year to a factor. Defaults to `FALSE`.
`period.factor`	Convert period to a factor. Defaults to `FALSE`.
`site.factor`	Convert site to a factor. Defaults to `FALSE`.
`trend`	The long-term linear trend on the log-scale.
`sd.rw.year`	The standard deviation of the year effects on the log-scale.
`amplitude.period`	The amplitude of the periodic effect on the log-scale.
`mean.phase.period`	The mean of the phase of the periodic effect among years. Defaults to `0`.
`sd.phase.period`	The standard deviation of the phase of the periodic effect among years.
`sd.site`	The standard deviation of the site effects on the log-scale.
`sd.rw.site`	The standard deviation of the random walk along year per site on the log-scale.
`sd.noise`	The standard deviation of the noise effects on the log-scale.
`size`	The size parameter of the negative binomial distribution.
`n.run`	The number of runs with the same mu.
`as.list`	Return the dataset as a list rather than a data.frame. Defaults to `FALSE`.
`details`	Add variables containing the year, period and site effects. Defaults tot `FALSE`.
`dataset`	A dataset to a the observation with missing data.
`proportion`	The proportion of observations that will be missing.
`count.variable`	The name of the variable holding the counts.
`observed.variable`	The name of the variable holding the observed values = either count or missing.
`site.variable`	The name of the variable holding the sites.
`year.variable`	The name of the variable holding the years.
`period.variable`	The name of the variable holding the period.
`max.count`	The maximum count.