Returns an BETA distribution object that produce random numbers
from a beta distribution using the rbeta
function
Usage
new_BETA(p_shape1, p_shape2, p_dimnames = "rvar")
new_BETA_lci(p_mean, p_lci, p_uci, p_dimnames = "rvar")
new_BETA_lci2(p_mean, p_lci, p_uci, p_dimnames = "rvar")
Arguments
- p_shape1
non-negative parameters of the Beta distribution
- p_shape2
non-negative parameters of the Beta distribution
- p_dimnames
A character that represents the name of the dimension
- p_mean
A numeric that represents the expected value of the proportion
- p_lci
A numeric for the lower 95% confidence interval
- p_uci
A numeric for the upper 95% confidence interval
Functions
new_BETA_lci()
: Constructor based on confidence intervals. Preserve expected value.new_BETA_lci2()
: Constructor based on ML confidence intervals
Note
When using confidence intervals, the shape parameters are obtained using the following formula:
\(varp = (p_uci-p_lci)/4^2\)
\(shape1 = p_mean * (p_mean * (1 - p_mean) / varp - 1)\)
\(shape2 =(1 - p_mean) * (p_mean * (1 - p_mean) / varp - 1) \)
new_BETA_lci2 estimate parameters using maximum likelihood myDistr <- new_BETA_lci2(0.30,0.25,0.35) myDistr$rfunc(10)
Examples
myDistr <- new_BETA(1,1)
myDistr$rfunc(10)
#> rvar
#> 1 0.16566696
#> 2 0.84279156
#> 3 0.53360650
#> 4 0.71023276
#> 5 0.22747849
#> 6 0.82505937
#> 7 0.67961427
#> 8 0.80433017
#> 9 0.93633854
#> 10 0.02445216
myDistr <- new_BETA_lci(0.30,0.25,0.35)
myDistr$rfunc(10)
#> rvar
#> 1 0.3184059
#> 2 0.2510281
#> 3 0.3148597
#> 4 0.2428678
#> 5 0.2852765
#> 6 0.2985150
#> 7 0.3157819
#> 8 0.2738824
#> 9 0.3135334
#> 10 0.3104217