midks.test: Kolmogorov-Smirnov Test assessing a Parametric Mixture for a...

In acid: Analysing Conditional Income Distributions

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.

Author(s)

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

acid documentation built on May 1, 2019, 10:14 p.m.