midks.test {acid} R Documentation

## Kolmogorov-Smirnov Test assessing a Parametric Mixture for a Conditional Income Distribution

### Description

This function performs a Kolmogorov-Smirnov test for a parametrically specified cdf composed of a mixture distribution either by cdf.mix.dag or cdf.mix.LN.

### Usage

```midks.test(x, y, ..., w = NULL, pmt = NULL)
```

### Arguments

 `x` a vector of observed incomes. `y` a function specifying the parametric cdf. `...` arguments to be passed to y. `w` the weights of the observations contained in y. `pmt` point mass threshold equivalent to thres0 in y.

### Value

 `statistic` returns the test statistic. `method` returns the methodology - currently always One-sample KS-test. `diffpm` the difference of the probability for the point mass. `diff1` the upper difference between for the continuous part of the cdfs. `diff2` the lower difference between for the continuous part of the cdfs.

Alexander Sohn

### References

Sohn, A., Klein, N. and Kneib. T. (2014): A New Semiparametric Approach to Analysing Conditional Income Distributions, in: SOEPpapers, No. 676.

### Examples

```# parameter values
pi0.s<-0.2
pi1.s<-0.1
thres0.s<-0
thres1.s<-25000
mu.s<-20000
sigma.s<-5
nu.s<-0.5
tau.s<-1

# generate sample
n<-100
s<-as.data.frame(matrix(NA,n,3))
names(s)<-c("cat","y","w")
s[,1]<-sample(1:3,n,replace=TRUE,prob=c(pi0.s,pi1.s,1-pi0.s-pi1.s))
s[,3]<-rep(1,n)
for(i in 1:n){
if(s\$cat[i]==1){s\$y[i]<-0
}else if(s\$cat[i]==2){s\$y[i]<-runif(1,thres0.s,thres1.s)
}else s\$y[i]<-rGB2(1,mu=mu.s,sigma=sigma.s,nu=nu.s,tau=tau.s)+thres1.s
}

# midks.test
midks.test(s\$y,cdf.mix.dag,pi0=pi0.s,thres0=thres0.s,pi1=pi1.s,thres1=thres1.s,mu=mu.s,
sigma=sigma.s,nu=nu.s,tau=tau.s,w=s\$w,pmt=thres0.s)\$statistic

```

[Package acid version 1.1 Index]