| pzigp {ZIGP} | R Documentation |
'pzigp' calculates the distribution function of the ZIGP distribution.
pzigp(x, mu, phi, omega)
x |
vector of discrete points |
mu |
mean |
phi |
dispersion parameter |
omega |
zero inflation parameter |
Calculates a vector of the same length as of x evaluating the ZIGP distribution function at x.
x <- 1:10
pzigp(x, 2, 1.5, 0.2)
#[1] 0.6123450 0.7567027 0.8505619 0.9091225 0.9449692 0.9667183 0.9798649
#[8] 0.9878036 0.9925998 0.9955013
## The function is currently defined as
function(x, mu = stop("no mu arg"), phi = stop("no phi arg"),
omega = stop("no omega arg")){
# check if parameters are valid
if(omega < 0) {return("omega has to be in [0,1]!")}
if(omega > 1) {return("omega has to be in [0,1]!")}
upper <- max(x)
s <- double(upper+1)
#P(X=0)
p <- omega + (1-omega) * exp(-mu/phi)
s[1] <- p
if (upper > 0) {
rekursive <- FALSE
for (i in 1:upper) {
#P(X=x)
if (rekursive==FALSE) {
p <- (1-omega)*mu*(mu+(phi-1)*i)^(i-1)/exp(lgamma(i+1))*
phi^(-i)*exp(-1/phi*(mu+(phi-1)*i))}
if (p==Inf) {
rekursive <- TRUE
log.p.alt <- log( (1-omega)*mu*(mu+(phi-1)*(i-1))^(i-2)/
exp(lgamma(i-1+1))*
phi^(-(i-1))*exp(-1/phi*(mu+(phi-1)*(i-1))))
}
if (rekursive==TRUE) {
log.p <- log( (mu+(i-1)*(phi-1))/(phi*i)*
(1+(phi-1)/(mu+(i-1)*(phi-1)))^(i-1)*
exp(1/phi-1) ) + log.p.alt
log.p.alt <- log.p
p <- exp(log.p)
}
s[i+1] <- s[i] + p
}
}
s2 <- double(length(x))
for (i in 1:length(x)) {
s2[i] <- s[x[i]+1]
}
return(s2)
}