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
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