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) }