estdweibull {DiscreteWeibull} R Documentation

## Estimation of parameters

### Description

Estimation of the parameters of the type 1 discrete Weibull distribution

### Usage

estdweibull(x, method = "ML", zero = FALSE, eps = 1e-04, nmax=1000)


### Arguments

 x the vector of sample values method "ML" for the maximum likelihood method; "M" for the method of moments; "P" for the method of proportions zero TRUE, if the support contains 0; FALSE otherwise eps error threshold for the computation of the moments of the distribution nmax maximum value considered for the numerical computation of the expected value

### Value

the vector of the estimates of q and \beta

### Author(s)

Alessandro Barbiero

ddweibull

### Examples

# Ex1
n <- 10
q <- 0.5
beta <- 0.8
x <- rdweibull(n, q, beta)
estdweibull(x, "ML") # maximum likelihood method
# it may return some harmless warnings
# that depend on the optimization function used in the maximization routine
estdweibull(x, "M") # method of moments
estdweibull(x, "P") # method of proportion
# the estimates provided by the three methods may be quite different
# from the true values... and to each other
# change the sample size
n <- 50
q <- 0.5
beta <- 0.8
x <- rdweibull(n, q, beta)
estdweibull(x, "ML") # maximum likelihood method
estdweibull(x, "M") # method of moments
estdweibull(x, "P") # method of proportion
# the estimates should be (on average) closer to the true values
# ...and to each other

# When the estimation methods fail...
# Ex2
# only 1s and 2s
x <- c(1,1,1,1,1,1,2,2,2,2)
estdweibull(x, "ML") # fails!
estdweibull(x, "M") # fails!
estdweibull(x, "P") # fails!

# Ex3
# no 1s
x <- c(2,2,3,4,5,5,5,6,6,8,10)
estdweibull(x, "ML") # works
estdweibull(x, "M") # works
estdweibull(x, "P") # fails!


[Package DiscreteWeibull version 1.1 Index]