estdweibull: Estimation of parameters
In DiscreteWeibull: Discrete Weibull Distributions (Type 1 and 3)

Description Usage Arguments Value Author(s) See Also Examples

View source: R/estdweibull.R

Estimation of the parameters of the type 1 discrete Weibull distribution

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

`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

the vector of the estimates of q and β

Alessandro Barbiero

ddweibull

# 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!