# 3/3/10
# ---------------------------------------------------------------------------------------
# zero inflated Poisson inverse Gaussian (with probability y=0 is nu) 20/04/10
# ---------------------------------------------------------------------------------------
ZIPIG = function (mu.link = "log", sigma.link = "log", nu.link = "logit")
{
mstats <- checklink("mu.link", "ZIPIG", substitute(mu.link),
c("inverse", "log", "identity"))
dstats <- checklink("sigma.link", "ZIPIG", substitute(sigma.link),
c("inverse", "log", "identity"))
vstats <- checklink("nu.link", "ZIPIG", substitute(nu.link),
c("logit", "probit", "cloglog", "log", "own"))
structure(list(family = c("ZIPIG", "Zero inflated Poisson inverse Gaussian"),
parameters = list(mu = TRUE, sigma = TRUE, nu = TRUE),
nopar = 3,
type = "Discrete",
mu.link = as.character(substitute(mu.link)),
sigma.link = as.character(substitute(sigma.link)),
nu.link = as.character(substitute(nu.link)),
mu.linkfun = mstats$linkfun,
sigma.linkfun = dstats$linkfun,
nu.linkfun = vstats$linkfun,
mu.linkinv = mstats$linkinv,
sigma.linkinv = dstats$linkinv,
nu.linkinv = vstats$linkinv,
mu.dr = mstats$mu.eta,
sigma.dr = dstats$mu.eta,
nu.dr = vstats$mu.eta,
dldm = function(y,mu,sigma,nu) {dldm0 <- (1-nu)*((nu+(1-nu)*dPIG(0,mu,sigma))^(-1))*dPIG(0,mu,sigma)*PIG()$dldm(0,mu,sigma)
dldm <- ifelse(y==0, dldm0, PIG()$dldm(y,mu,sigma))
dldm},
d2ldm2 = function(y,mu,sigma,nu) {dldm0 <- (1-nu)*((nu+(1-nu)*dPIG(0,mu,sigma))^(-1))*dPIG(0,mu,sigma)*PIG()$dldm(0,mu,sigma)
dldm <- ifelse(y==0, dldm0, PIG()$dldm(y,mu,sigma))
d2ldm2 <- -dldm*dldm
d2ldm2 <- ifelse(d2ldm2 < -1e-15, d2ldm2,-1e-15)
d2ldm2},
dldd = function(y,mu,sigma,nu) {dldd0 <- (1-nu)*((nu+(1-nu)*dPIG(0,mu,sigma))^(-1))*dPIG(0,mu,sigma)*PIG()$dldd(0,mu,sigma)
dldd <- ifelse(y==0, dldd0, PIG()$dldd(y,mu,sigma))
dldd},
d2ldd2 = function(y,mu,sigma,nu) {dldd0 <- (1-nu)*((nu+(1-nu)*dPIG(0,mu,sigma))^(-1))*dPIG(0,mu,sigma)*PIG()$dldd(0,mu,sigma)
dldd <- ifelse(y==0, dldd0, PIG()$dldd(y,mu,sigma))
d2ldd2 <- -dldd^2
d2ldd2 <- ifelse(d2ldd2 < -1e-15, d2ldd2,-1e-15)
d2ldd2},
dldv = function(y,mu,sigma,nu) {dldv0 <- ((nu+(1-nu)*dPIG(0,mu,sigma))^(-1))*(1-dPIG(0,mu,sigma))
dldv <- ifelse(y==0, dldv0, -1/(1-nu))
dldv},
d2ldv2 = function(y,mu,sigma,nu) {dldv0 <- ((nu+(1-nu)*dPIG(0,mu,sigma))^(-1))*(1-dPIG(0,mu,sigma))
dldv <- ifelse(y==0, dldv0, -1/(1-nu))
d2ldv2 <- -dldv^2
d2ldv2 <- ifelse(d2ldv2 < -1e-15, d2ldv2,-1e-15)
d2ldv2},
d2ldmdd = function(y,mu,sigma,nu) {dldm0 <- (1-nu)*((nu+(1-nu)*dPIG(0,mu,sigma))^(-1))*dPIG(0,mu,sigma)*PIG()$dldm(0,mu,sigma)
dldm <- ifelse(y==0, dldm0, PIG()$dldm(y,mu,sigma))
dldd0 <- (1-nu)*((nu+(1-nu)*dPIG(0,mu,sigma))^(-1))*dPIG(0,mu,sigma)*PIG()$dldd(0,mu,sigma)
dldd <- ifelse(y==0, dldd0, PIG()$dldd(y,mu,sigma))
d2ldm2<--dldm*dldd
d2ldm2},
d2ldmdv = function(y,mu,sigma,nu) { #partial derivate of log-density respect to mu and alpha
dldm0 <- (1-nu)*((nu+(1-nu)*dPIG(0,mu,sigma))^(-1))*dPIG(0,mu,sigma)*PIG()$dldm(0,mu,sigma)
dldm <- ifelse(y==0, dldm0, PIG()$dldm(y,mu,sigma))
dldv0 <- ((nu+(1-nu)*dPIG(0,mu,sigma))^(-1))*(1-dPIG(0,mu,sigma))
dldv <- ifelse(y==0, dldv0, -1/(1-nu))
d2ldmdv <- -dldm*dldv
d2ldmdv
},
d2ldddv = function(y,mu,sigma,nu) { #partial derivate of log-density respect to sigma and alpha
dldd0 <- (1-nu)*((nu+(1-nu)*dPIG(0,mu,sigma))^(-1))*dPIG(0,mu,sigma)*PIG()$dldd(0,mu,sigma)
dldd <- ifelse(y==0, dldd0, PIG()$dldd(y,mu,sigma))
dldv0 <- ((nu+(1-nu)*dPIG(0,mu,sigma))^(-1))*(1-dPIG(0,mu,sigma))
dldv <- ifelse(y==0, dldv0, -1/(1-nu))
d2ldddv <- -dldd*dldv
d2ldddv
},
G.dev.incr = function(y,mu,sigma,nu,...) -2*dZIPIG(y, mu = mu, sigma = sigma, nu=nu, log = TRUE),
rqres = expression(
rqres(pfun="pZIPIG", type="Discrete", ymin=0, y=y, mu=mu, sigma=sigma, nu=nu)
),
mu.initial = expression(mu <- (y + mean(y))/2),
## mu.initial = expression(mu <- y+0.5),
sigma.initial = expression(
sigma <- rep( max( ((var(y)-mean(y))/(mean(y)^2)),0.1),length(y))),
nu.initial = expression(nu <- rep(0.1, length(y))),#expression(nu <- rep(((sum(y==0)/length(y))+0.01)/2, length(y))),#expression(nu <- rep(0.3, length(y))),
mu.valid = function(mu) all(mu > 0) ,
sigma.valid = function(sigma) all(sigma > 0),
nu.valid = function(nu) all(nu > 0 & nu < 1),
y.valid = function(y) all(y >= 0),
mean = function(mu, sigma, nu) (1- nu) * mu,
variance = function(mu, sigma, nu) mu * (1 - nu) + mu^2 * (1 - nu) * (sigma + nu)
),
class = c("gamlss.family","family"))
}
#-------------------------------------------------------------------------------------------
dZIPIG<-function(x, mu = 1, sigma = 1, nu = 0.3, log = FALSE)
{
if (any(mu <= 0) ) stop(paste("mu must be greater than 0 ", "\n", ""))
if (any(sigma <= 0) ) stop(paste("sigma must be greater than 0 ", "\n", ""))
if (any(nu <= 0)|any(nu >= 1)) stop(paste("nu must be between 0 and 1 ", "\n", ""))
if (any(x < 0) ) stop(paste("x must be >=0", "\n", ""))
ly <- max(length(x),length(mu),length(sigma),length(nu))
x <- rep(x, length = ly)
sigma <- rep(sigma, length = ly)
mu <- rep(mu, length = ly)
nu <- rep(nu, length = ly)
if (length(sigma)>1) fy <- ifelse(sigma>0.0001, dPIG(x, mu = mu, sigma=sigma, log = T),
dPO(x, mu = mu, log = T) )
else fy <- if (sigma<0.0001) dPO(x, mu = mu, log = T)
else dPIG(x, mu = mu, sigma=sigma, log = T)
logfy <- rep(0, length(x))
logfy <- ifelse((x==0), log(nu+(1-nu)*exp(fy)), (log(1-nu) + fy ))
if(log == FALSE) fy2 <- exp(logfy) else fy2 <- logfy
fy2
}
#------------------------------------------------------------------------------------------
pZIPIG <- function(q, mu = 1, sigma = 1, nu = 0.3, lower.tail = TRUE, log.p = FALSE)
{
if (any(mu <= 0) ) stop(paste("mu must be greater than 0 ", "\n", ""))
if (any(sigma <= 0) ) stop(paste("sigma must be greater than 0 ", "\n", ""))
if (any(nu <= 0)|any(nu >= 1)) #In this parametrization nu = alpha
stop(paste("nu must be between 0 and 1 ", "\n", ""))
if (any(q < 0) ) stop(paste("y must be >=0", "\n", ""))
ly <- max(length(q),length(mu),length(sigma),length(nu))
q <- rep(q, length = ly)
sigma <- rep(sigma, length = ly)
mu <- rep(mu, length = ly)
nu <- rep(nu, length = ly)
if (length(sigma)>1) cdf <- ifelse(sigma>0.0001, pPIG(q, mu = mu, sigma=sigma, lower.tail=T, log.p = F),
ppois(q, lambda = mu) )
else cdf <- if (sigma<0.0001) ppois(q, lambda = mu)
else pPIG(q, mu = mu, sigma=sigma, lower.tail=T, log.p = F)
cdf <- nu + (1-nu)*cdf
if(lower.tail == TRUE) cdf <- cdf else cdf <-1-cdf
if(log.p==FALSE) cdf <- cdf else cdf <- log(cdf)
cdf
}
#------------------------------------------------------------------------------------------
qZIPIG <- function(p, mu = 1, sigma = 1, nu = 0.3, lower.tail = TRUE, log.p = FALSE,
max.value = 10000)
{
if (any(mu <= 0) ) stop(paste("mu must be greater than 0 ", "\n", ""))
if (any(sigma <= 0) ) stop(paste("sigma must be greater than 0 ", "\n", ""))
if (any(nu <= 0)|any(nu >= 1)) #In this parametrization nu = alpha
stop(paste("nu must be between 0 and 1 ", "\n", ""))
if (any(p < 0) | any(p > 1)) stop(paste("p must be between 0 and 1", "\n", ""))
if (log.p == TRUE) p <- exp(p) else p <- p
if (lower.tail == TRUE) p <- p else p <- 1 - p
ly <- max(length(p),length(mu),length(sigma),length(nu))
p <- rep(p, length = ly)
sigma <- rep(sigma, length = ly)
mu <- rep(mu, length = ly)
nu <- rep(nu, length = ly)
pnew <- (p-nu)/(1-nu)-1e-10
pnew <- ifelse((pnew > 0 ),pnew, 0)
if (length(sigma)>1) q <- ifelse(sigma>0.0001, qPIG(pnew, mu = mu, sigma=sigma, lower.tail=TRUE, log.p = FALSE, max.value = max.value),
qpois(pnew, lambda = mu) )
else q <- if (sigma<0.0001) qpois(pnew, lambda = mu)
else qPIG(pnew, mu = mu, sigma=sigma, lower.tail=TRUE, log.p = FALSE, max.value = max.value)
# q2 <- suppressWarnings(ifelse((pnew > 0 ), q, 0))
# suppressWarnings(q <- ifelse((pnew > 0 ), qpois(pnew, lambda = mu, ), 0))
q
}
#------------------------------------------------------------------------------------------
rZIPIG <- function(n, mu = 1, sigma = 1, nu = 0.3, max.value = 10000)
{
if (any(mu <= 0) ) stop(paste("mu must be greater than 0 ", "\n", ""))
if (any(sigma <= 0) ) stop(paste("sigma must be greater than 0 ", "\n", ""))
if (any(nu <= 0)|any(nu >= 1)) #In this parametrization nu = alpha
stop(paste("nu must be between 0 and 1 ", "\n", ""))
if (any(n <= 0)) stop(paste("n must be a positive integer", "\n", ""))
n <- ceiling(n)
p <- runif(n)
r <- qZIPIG(p, mu=mu, sigma=sigma, nu=nu)
r
}
#------------------------------------------------------------------------------------------
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