summary.zigp {ZIGP} | R Documentation |
Summary
Description
'summary.zigp' summarizes the results of the maximum likelihood estimation.
Usage
summary.zigp(mle.data.in)
Arguments
mle.data.in |
a list of result parameters given by function 'mle.zigp' |
Examples
## The function is currently defined as
function(mle.data.in)
{
X <- mle.data.in$Design.Mu
if(is.matrix(X)) {
nx <- dim(X)[1]
k.beta <- dim(X)[2]
}
else {
nx <- length(X)
k.beta <- 1
}
W <- mle.data.in$Design.Phi
if(is.matrix(W)) {
nw <- dim(W)[1]
k.alpha <- dim(W)[2]
}
else {
nw <- length(W)
k.alpha <- 1
}
Z <- mle.data.in$Design.Omega
if(is.matrix(Z)) {
nz <- dim(Z)[1]
k.gamma <- dim(Z)[2]
}
else {
nz <- length(Z)
k.gamma <- 1
}
# range of ZI parameters
out0 <- matrix(double(2), 1, 2)
out0[1, 1] <- min(mle.data.in$ZI.Parameter)
out0[1, 2] <- max(mle.data.in$ZI.Parameter)
colnames(out0) <- c("", "")
rownames(out0) <- c("Range for ZI-Parameters: ")
print(out0)
# range of Dispersion Parameters
out1 <- matrix(double(2), 1, 2)
out1[1, 1] <- min(mle.data.in$Dispersion.Parameter)
out1[1, 2] <- max(mle.data.in$Dispersion.Parameter)
colnames(out1) <- c("", "")
rownames(out1) <- c("Range of Dispersion Pars: ")
print(out1)
# beta
out2 <- matrix(double(k.beta), 1, k.beta)
kopf <- rep("", k.beta)
for(i in 1:k.beta) {
out2[1, i] <- mle.data.in$Coefficients.Mu[i]
}
colnames(out2) <- kopf
rownames(out2) <- c("Coefficients for mu: ")
print(out2)
# alpha
out3 <- matrix(double(k.alpha), 1, k.alpha)
kopf <- rep("", k.alpha)
for(i in 1:k.alpha) {
out3[1, i] <- mle.data.in$Coefficients.Phi[i]
}
colnames(out3) <- kopf
rownames(out3) <- c("Coefficients for phi: ")
print(out3)
# gamma
out4 <- matrix(double(k.gamma), 1, k.gamma)
kopf <- rep("", k.gamma)
for(i in 1:k.gamma) {
out4[1, i] <- mle.data.in$Coefficients.Omega[i]
}
colnames(out4) <- kopf
rownames(out4) <- c("Coefficients for omega: ")
print(out4)
# Pearson Chi Squared
out5 <- matrix(double(1), 1, 1)
out5[1, 1] <- mle.data.in$Pearson
colnames(out5) <- c("")
rownames(out5) <- c("Pearson Chi Squared: ")
print(out5)
# range of mu
out6 <- matrix(double(2), 1, 2)
out6[1, 1] <- mle.data.in$Range.Mu[1]
out6[1, 2] <- mle.data.in$Range.Mu[2]
colnames(out6) <- c("", "")
rownames(out6) <- c("Range of mu: ")
print(out6)
# optimization message
out7 <- matrix(double(1), 1, 1)
out7[1, 1] <- mle.data.in$Message
colnames(out7) <- c("")
rownames(out7) <- c("Message: ")
print(out7)
# AIC
out8 <- matrix(double(1), 1, 1)
out8[1, 1] <- mle.data.in$AIC
colnames(out8) <- c("")
rownames(out8) <- c("AIC: ")
print(out8)
return()
}
[Package
ZIGP version 1.1
Index]