Generate data from a density defined by a vector of integers

Source: R/generate_data.R

Data are generated from an a density defined by a vector of integers

genDataDensity(
  n,
  dataDist,
  varname,
  uselimits = FALSE,
  id = "id",
  na.rm = TRUE
)

Arguments

n

Integer. Number of samples to draw from the density.

dataDist

Numeric vector. Defines the desired density.

varname

Character. Name of the variable.

uselimits

Logical. If TRUE, the minimum and maximum of the input data vector are used as limits for sampling. Defaults to FALSE, in which case a smoothed density that extends beyond these limits is used.

id

Character. A string specifying the field that serves as the record ID. The default field is "id".

na.rm

Logical. If TRUE (default), missing values in `dataDist` are removed. If FALSE, the data will retain the same proportion of missing values.

Value

A data table with the generated data

Examples

data_dist <- c(1, 2, 2, 3, 4, 4, 4, 5, 6, 6, 7, 7, 7, 8, 9, 10, 10)

genDataDensity(500, data_dist, varname = "x1", id = "id")
#> Key: <id>
#>         id        x1
#>      <int>     <num>
#>   1:     1  6.921986
#>   2:     2  3.706854
#>   3:     3  9.234597
#>   4:     4  6.103531
#>   5:     5 10.658962
#>  ---                
#> 496:   496  6.691994
#> 497:   497  6.571446
#> 498:   498 10.888954
#> 499:   499  7.930779
#> 500:   500  5.261284
genDataDensity(500, data_dist, varname = "x1", uselimits = TRUE, id = "id")
#> Key: <id>
#>         id       x1
#>      <int>    <num>
#>   1:     1 2.379838
#>   2:     2 6.618362
#>   3:     3 3.917192
#>   4:     4 7.605761
#>   5:     5 5.332133
#>  ---               
#> 496:   496 6.368137
#> 497:   497 6.432943
#> 498:   498 7.343834
#> 499:   499 9.681368
#> 500:   500 4.174617