weibull_plt: Weibull coefficients of power-law transformed Weibull
In distributionsrd: Distribution Fitting and Evaluation

Description Usage Arguments Details Value

Coefficients of a power-law transformed Weibull distribution

1	weibull_plt(scale = 1, shape = 2, a = 1, b = 1, inv = FALSE)

`shape, scale`	shape and scale of the distribution with default values of 2 and 1 respectively.
`a, b`	constant and power of power-law transformation, defaults to 1 and 1 respectively.
`inv`	logical indicating whether coefficients of the outcome variable of the power-law transformation should be returned (FALSE) or whether coefficients of the input variable being power-law transformed should be returned (TRUE). Defaults to FALSE.

If the random variable y is Weibull distributed with mean meanlog and standard deviation sdlog, then the power-law transformed variable

y = ax^b

is Weibull distributed with scale ( \frac{scale}{a})^{\frac{1}{b}} and shape b*shape.

Returns a named list containing

coefficients: Named vector of coefficients

## Comparing probabilites of power-law transformed transformed variables pweibull(3,shape=2,scale=1) coeff = weibull_plt(shape=2,scale=1,a=5,b=7)$coefficients pweibull(5*3^7,shape=coeff[["shape"]],scale=coeff[["scale"]])

pweibull(5*0.8^7,shape=2,scale=1) coeff = weibull_plt(shape=2,scale=1,a=5,b=7,inv=TRUE)$coefficients pweibull(0.8,shape=coeff[["shape"]],scale=coeff[["scale"]])

## Comparing the first moments and sample means of power-law transformed variables for large enough samples x = rweibull(1e5,shape=2,scale=1) coeff = weibull_plt(shape=2,scale=1,a=2,b=0.5)$coefficients y = rweibull(1e5,shape=coeff[["shape"]],scale=coeff[["scale"]]) mean(2*x^0.5) mean(y) mweibull(r=1,shape=coeff[["shape"]],scale=coeff[["scale"]],lower.tail=FALSE)

distributionsrd documentation built on July 1, 2020, 10:21 p.m.