Create random distribution based on configuration file

This function does the same thing as kwb.utils::generate_random_values(), but it is bundled with ambre to avoid a hard dependency on the unmaintained package.

Usage

generate_random_values(
  config,
  number_of_repeatings = 1,
  number_of_events,
  debug = TRUE
)

Arguments

config

as retrieved by config_read()

number_of_repeatings

how often should the random distribution with the same parameters be generated (default: 1)

number_of_events

number of events

debug

print debug information (default: TRUE)

Value

list random distributions based on configuration file

References

Sonnenberg H (2024). kwb.utils: General Utility Functions Developed at KWB. R package version 0.15.0 URL: https://github.com/kwb-r/kwb.utils (MIT Licence)

Examples

# Example usage of generate_random_values
# Create a sample config object
config <- list(
  type = "norm",
  value = 10,
  min = 5,
  max = 15,
  mean = 10,
  sd = 2,
  meanlog = log(10),
  sdlog = 0.5,
  mode = 10
)

# Call generate_random_values with the sample config
result <- generate_random_values(
  config = config,
  number_of_repeatings = 2,
  number_of_events = 10,
  debug = FALSE
)

# Print the results
cat("Simulated events:")
#> Simulated events:
print(result$events)
#>    repeatID eventID    values
#> 1         1       1 12.780708
#> 2         1       2  9.628517
#> 3         1       3  8.229293
#> 4         1       4 11.115832
#> 5         1       5 11.977835
#> 6         1       6  9.846005
#> 7         1       7 10.132986
#> 8         1       8  8.069863
#> 9         1       9  9.396153
#> 10        1      10 11.357362
#> 11        2       1 13.506611
#> 12        2       2  7.435721
#> 13        2       3  9.008389
#> 14        2       4  8.257585
#> 15        2       5  9.087613
#> 16        2       6 10.664732
#> 17        2       7  8.812670
#> 18        2       8 11.515820
#> 19        2       9  8.639734
#> 20        2      10 12.113586

cat("Parameters used for simulation:")
#> Parameters used for simulation:
print(result$paras)
#>   type repeatings events mean sd
#> 1 norm          2     10   10  2