ex2.sim {bivpois} | R Documentation |
The data has one pair (x,y) of diagonal inflated bivariate Poisson variables and five variables (z1,…,z5) generated from N(0, 0.12) distribution. Hence Xi, Yi ~ DIBP( lambda_1i, lambda_2i, lambda_3i , p=0.30, Poisson(2) ) loglambda_1i = 1.8 + 2 Z1i + 3 Z3i loglambda_2i = 0.7 – Z1i – 3 Z3i + 3 Z5i loglambda_3i = 1.7 + Z1i – 2 Z2i + 2 Z3i – 2 Z4i
data(ex2.sim)
A data frame with 100 observations on the following 7 variables.
This data is used as example one in Karlis and Ntzoufras (2004).
Karlis, D. and Ntzoufras, I. (2004). Bivariate Poisson and Diagonal Inflated Bivariate Poisson Regression Models in S. (submitted). Technical Report, Department of Statistics, Athens University of Economics and Business, Athens, Greece.
Karlis, D. and Ntzoufras, I. (2003). Analysis of Sports Data Using Bivariate Poisson Models. Journal of the Royal Statistical Society, D, (Statistician), 52, 381 – 393.
library(bivpois) # load bivpois library data(ex2.sim) # load ex2.sim data from bivpois library # # formula for lambda1 and lamba2 form1 <- y1y2~noncommon + z1:noncommon + z3 + I(l2*z5) # formula for lambda3 form2 <- y3~z1+z2+z3+z4 # # Model 1: BivPois ex2.m1 <-lm.bp ( 'x', 'y', form1, form2, data=ex2.sim) # Model 2: Zero Inflated BivPois ex2.m2 <-lm.dibp( 'x', 'y', form1, form2, data=ex2.sim, distribution='discrete', jmax=0 ) # Model 3: Diagonal Inflated BivPois with DISCRETE(1) diagonal inflation distribution ex2.m3 <-lm.dibp( 'x', 'y', form1, form2, data=ex2.sim, distribution='discrete', jmax=1 ) # Model 4: Diagonal Inflated BivPois with DISCRETE(2) diagonal inflation distribution ex2.m4 <-lm.dibp( 'x', 'y', form1, form2, data=ex2.sim, distribution='discrete', jmax=2 ) # Model 5: Diagonal Inflated BivPois with DISCRETE(3) diagonal inflation distribution ex2.m5 <-lm.dibp( 'x', 'y', form1, form2, data=ex2.sim, distribution='discrete', jmax=3 ) # Model 6: Diagonal Inflated BivPois with DISCRETE(4) diagonal inflation distribution ex2.m6 <-lm.dibp( 'x', 'y', form1, form2, data=ex2.sim, distribution='discrete', jmax=4 ) # Model 7: Diagonal Inflated BivPois with DISCRETE(5) diagonal inflation distribution ex2.m7 <-lm.dibp( 'x', 'y', form1, form2, data=ex2.sim, distribution='discrete', jmax=5 ) # Model 8: Diagonal Inflated BivPois with DISCRETE(6) diagonal inflation distribution ex2.m8 <-lm.dibp( 'x', 'y', form1, form2, data=ex2.sim, distribution='discrete', jmax=6 ) # Model 9: Diagonal Inflated BivPois with POISSON diagonal inflation distribution ex2.m9 <-lm.dibp( 'x', 'y', form1, form2, data=ex2.sim, distribution='poisson' ) # Model 10: Diagonal Inflated BivPois with GEOMETRIC diagonal inflation distribution ex2.m10<-lm.dibp( 'x', 'y', form1, form2, data=ex2.sim, distribution='geometric' ) # # printing parameters of model 7 ex2.m7$beta1 ex2.m7$beta2 ex2.m7$beta3 ex2.m7$p ex2.m7$theta # # printing parameters of model 9 ex2.m9$beta1 ex2.m9$beta2 ex2.m9$beta3 ex2.m9$p ex2.m9$theta