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Convert the summary statistics of a distribution to parameters

Source: R/convert_params.R
convert_summary_stats_to_params.Rd

Convert the summary statistics for a range of distributions to the distribution's parameters. Most summary statistics are calculated analytically given the parameters. An exception is the Weibull distribution which uses a root finding numerical method.

Usage

convert_summary_stats_to_params(x, ...)

# S3 method for class 'character'
convert_summary_stats_to_params(
  x = c("lnorm", "gamma", "weibull", "nbinom", "geom"),
  ...
)

# S3 method for class 'epiparameter'
convert_summary_stats_to_params(x, ...)

Arguments

x

An R object.

...

<dynamic-dots> Numeric named summary statistics used to convert to parameter(s). An example is the mean and sd summary statistics for the lognormal (lnorm) distribution.

Value

A list of either one or two elements (depending on how many parameters the distribution has).

Details

Summary statistics should be named accordingly (case-sensitive):

  • mean: mean

  • median: median

  • mode: mode

  • variance: var

  • standard deviation: sd

  • coefficient of variation: cv

  • skewness: skewness

  • excess kurtosis: ex_kurtosis

Note: Not all combinations of summary statistics can be converted into distribution parameters. In this case the function will error stating that the parameters cannot be calculated from the given input.

The distribution names and parameter names follow the style of distributions in R, for example the lognormal distribution is lnorm, and its parameters are meanlog and sdlog.

See also

convert_params_to_summary_stats()

Examples

# examples using characters
convert_summary_stats_to_params("lnorm", mean = 1, sd = 1)
#> $meanlog
#> [1] -0.3465736
#> 
#> $sdlog
#> [1] 0.8325546
#> 
convert_summary_stats_to_params("weibull", mean = 2, var = 2)
#> Numerical approximation used, results may be unreliable.
#> $shape
#> [1] 1.435521
#> 
#> $scale
#> [1] 2.202641
#> 
convert_summary_stats_to_params("geom", mean = 2)
#> $prob
#> [1] 0.3333333
#> 

# examples using <epiparameter>
epiparameter <- epiparameter_db(single_epiparameter = TRUE)
#> Using Linton N, Kobayashi T, Yang Y, Hayashi K, Akhmetzhanov A, Jung S, Yuan
#> B, Kinoshita R, Nishiura H (2020). “Incubation Period and Other
#> Epidemiological Characteristics of 2019 Novel Coronavirus Infections
#> with Right Truncation: A Statistical Analysis of Publicly Available
#> Case Data.” _Journal of Clinical Medicine_. doi:10.3390/jcm9020538
#> <https://doi.org/10.3390/jcm9020538>.. 
#> To retrieve the citation use the 'get_citation' function
convert_summary_stats_to_params(epiparameter)
#> $meanlog
#> [1] 0.9466094
#> 
#> $sdlog
#> [1] 1.628199
#> 

# example using <epiparameter> and specifying summary stats
epiparameter$summary_stats <- list()
convert_summary_stats_to_params(epiparameter, mean = 10, sd = 2)
#> $meanlog
#> [1] 2.282975
#> 
#> $sdlog
#> [1] 0.1980422
#>