# lossdiw: Loss function In DiscreteInverseWeibull: Discrete Inverse Weibull Distribution

## Description

Quadratic loss function for the method of moments

## Usage

 `1` ```lossdiw(x, par, eps = 1e-04, nmax=1000) ```

## Arguments

 `x` a vector of sample values `par` a vector of parameters (q and β) `eps` a tolerance error for the computation of first order moments `nmax` a first maximum value for the computation of first order moments

## Value

the value of the quadratic loss function L(x; q, β)=(E(X; q, β)-m_1)^2+(E(X^2; q, β)-m_2)^2 where m_1 and m_2 are the first and second order sample moments.

`Ediweibull`
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13``` ```n<-100 q<-0.5 beta<-2.5 x<-rdiweibull(n, q, beta) # loss function computed on the true values lossdiw(x, c(q, beta)) par<-estdiweibull(x, method="M") # estimates of the parameters through the method of moments par # loss function computed on the estimates derived through # the method of moments lossdiw(x, par) # it should be zero (however, smaller than before...) ```