ex2.sim {bivpois} | R Documentation |
The data has one pair $(x,y)$ of diagonal inflated bivariate Poisson variables and five variables $(z_1,...,z_5)$ generated from $N(0, 0.12)$ distribution. Hence
hspace{1cm} $X_i, Y_i sim DIBP( λ_{1i}, λ_{2i}, λ_{3i} , p=0.30, Poisson(2) ) $ with
hspace{2cm} $logλ_{1i} = 1.8 + 2 Z_{1i} + 3 Z_{3i}$
hspace{2cm} $logλ_{2i} = 0.7 - Z_{1i} - 3 Z_{3i} + 3 Z_{5i}$
hspace{2cm} $logλ_{3i} = 1.7 + Z_{1i} - 2 Z_{2i} + 2 Z_{3i} - 2 Z_{4i}.$
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).
1. Karlis, D. and Ntzoufras, I. (2005). Bivariate Poisson and Diagonal Inflated Bivariate Poisson Regression Models in R. Journal of Statistical Software (to appear).
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.
# Models of example 2 can be fitted using the command # demo(ex2, package='bivpois') # # Here we present the same commands but iterations of the EM were restricted to 2 to save time library(bivpois) # load bivpois library data(ex2.sim) # load ex2.sim data from bivpois library # # Model 1: BivPois ex2.m1<-lm.bp( x~z1 , y~z1+z5, l1l2=~z3, l3=~.-z5, data=ex2.sim, maxit=2 ) # Model 2: Zero Inflated BivPois ex2.m2<-lm.dibp( x~z1 , y~z1+z5, l1l2=~z3, l3=~.-z5, data=ex2.sim , jmax=0, maxit=2 ) # Model 3: Diagonal Inflated BivPois with DISCRETE(1) diagonal distribution ex2.m3<-lm.dibp( x~z1 , y~z1+z5, l1l2=~z3, l3=~.-z5, data=ex2.sim , jmax=1, maxit=2 ) # Model 4: Diagonal Inflated BivPois with DISCRETE(2) diagonal distribution ex2.m4<-lm.dibp( x~z1 , y~z1+z5, l1l2=~z3, l3=~.-z5, data=ex2.sim , jmax=2, maxit=2 ) # Model 5: Diagonal Inflated BivPois with DISCRETE(3) diagonal distribution ex2.m5<-lm.dibp( x~z1 , y~z1+z5, l1l2=~z3, l3=~.-z5, data=ex2.sim , jmax=3, maxit=2 ) # Model 6: Diagonal Inflated BivPois with DISCRETE(4) diagonal distribution ex2.m6<-lm.dibp( x~z1 , y~z1+z5, l1l2=~z3, l3=~.-z5, data=ex2.sim , jmax=4, maxit=2 ) # Model 7: Diagonal Inflated BivPois with DISCRETE(5) diagonal distribution ex2.m7<-lm.dibp( x~z1 , y~z1+z5, l1l2=~z3, l3=~.-z5, data=ex2.sim , jmax=5, maxit=2 ) # Model 8: Diagonal Inflated BivPois with DISCRETE(6) diagonal distribution ex2.m8<-lm.dibp( x~z1 , y~z1+z5, l1l2=~z3, l3=~.-z5, data=ex2.sim , jmax=6, maxit=2 ) # Model 9: Diagonal Inflated BivPois with POISSON diagonal distribution ex2.m9<-lm.dibp( x~z1 , y~z1+z5, l1l2=~z3, l3=~.-z5, data=ex2.sim , distribution="poisson", maxit=2 ) # Model 10: Diagonal Inflated BivPois with GEOMETRIC diagonal distribution ex2.m10<-lm.dibp( x~z1 , y~z1+z5, l1l2=~z3, l3=~.-z5, data=ex2.sim , distribution="geometric", maxit=2 ) # # 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