[R] generate variable y to produce excess zero in ZIP analysis

S Ellison S.Ellison at LGCGroup.com
Wed Feb 20 15:03:25 CET 2013


> Subject: [R] generate variable y to produce excess zero in 
> ZIP analysis

Maybe something like

rzip <-  function(n, lambda, zip=0.0) {
	#zip is the desired proportion of _excess_ zeros
               if(zip>1.0 || zip <0) stop("zip must be in (0,1)")
               n.zip <- ceiling(zip*n)
               n.pois <- n-n.zip
              sample( c( rpois(n.pois, lambda), rep(0,n.zip) ) )
}

#Example
rzip(50, 3.5, zip=0.5)

Having said that, I'd bet there's a package out there that already does it better...

 S Ellison

> 
> 
> 
> Dear Mr/Mrs
> 
> I am Lili Puspita Rahayu, student from magister third level 
> of Statistics in Bogor Agriculture University. 
> Mr/
> Mrs, now I'm analyzing the Zero inflated Poisson (ZIP), which 
> is a solution of the Poisson regression where the response 
> variable (Y) has zero excess. ZIP now I was doing did not use 
> real data, but using simulated data in R. Simulations by 
> generating data on variables x1, x2, x3 with each size n = 
> 100, after which generate data on response variable (Y). 
> However, when I generate the variable y, after generating 
> variables x1, x2, x3, then the simulation result in the 
> variable y that does not have a zero excess. Sometimes just a 
> coincidence there are 23%, 25% the proportion of zero on the 
> variable Y. This is because I generate variables x1, x2, x3 
> with a distribution that has a small parameter values​​. I've 
> been consulting with my lecturer, and suggested to generate 
> variable Y that can control the proportion of zero on ​​ZIP 
> analysis. I've been trying to make the syntax, but has not 
> succeeded.I would like to ask for assistance to R to make the 
> syntax to generate simulated Y variables that can control the 
> proportion of zeros after generating variables x1, x2, x3 on 
> ZIP analysis.Thus, I can examine more deeply to determine how 
> much the proportion of zeros on response variable (Y) that 
> can be used in the Poisson regression analysis, parametric 
> ZIP and ZIP semiparametric.
> 
> syntax that I made previously by generating variable y 
> without being controlled to produce zero excess in R :
> 
> > b0=1.5
> > b1=-log(2)
> > b2=log(3)
> > b3=log(4)
> > n=100
> > x1<-rnorm(n, mean=5, sd=2)
> > x2<-runif(n, min=1, max=2)
> > x3<-rnorm(n, mean=10, sd=15)
> > 
> > y<-seq(1,n)
> > for(i in 1:n)
> + {
> + m<-exp(b0+b1*x1[i]+b2*x2[i]+b3*x3[i])
> + yp<-rpois(1,m)
> + y[i]<-yp
> + }
> 
> 
> I am very
> grateful for the assistance of R.
> I am looking forward to hearing from you. Thank you very much.
> 
> Sincerely yours
> Lili Puspita Rahayu 
> 	[[alternative HTML version deleted]]
> 
> 

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