weibull.wp: Estimate of shape and scale parameters of Weibull using the...

In weibullness: Goodness-of-Fit Test for Weibull Distribution (Weibullness)

Estimate of shape and scale parameters of Weibull using the Weibull plot

Description

Calculates the estimates of the shape and scale parameters.

Usage

weibull.wp(x, n, a)

Arguments

x	a numeric vector of observations.
n	The number of observations is needed if there is right-censoring.
a	the offset fraction to be used; typically in (0,1). See ppoints.

Details

weibull.wp obtains the estimates of the shape and scale parameters using the intercept and slope estimates from the Weibull plot.

Value

An object of class "weibull.estimate", a list with two parameter estimates

Author(s)

Chanseok Park

References

Park, C. (2018). A Note on the Existence of the Location Parameter Estimate of the Three-Parameter Weibull Model Using the Weibull Plot. Mathematical Problems in Engineering, 2018, 6056975.
\Sexpr[results=rd]{tools:::Rd_expr_doi("10.1155/2018/6056975")}

Park, C. (2017). Weibullness test and parameter estimation of the three-parameter Weibull model using the sample correlation coefficient. International Journal of Industrial Engineering - Theory, Applications and Practice, 24(4), 376-391.
\Sexpr[results=rd]{tools:::Rd_expr_doi("10.23055/ijietap.2017.24.4.2848")}

See Also

weibull.mle for the parameter estimation using the maximum likelihood method.

weibull.rm for robust parameter estimation using the repeated median method.

fitdistr for maximum-likelihood fitting of univariate distributions in package MASS.

Examples

library(weibullness)

data = c(355,725,884,462,1092,190,166,172,188,224,267,298,355,471,
        154,101,76,811,80,249,752,305,301,386,667,212,186,127,
        121,214,242,237,355,210,253,400,401,514,211,285)
weibull.wp(data)

weibullness documentation built on Aug. 8, 2023, 5:12 p.m.