Nothing
fix0201.obs <-
function (x, alpha = 2, beta = 1, iter = 60, converge = 1e-04)
{
if (var(x[, 2]) > 1e-10) {
warning("censoring values are not all the same")
}
realvalues <- x[x[, 2] < x[, 1], 1]
pqlvalues <- x[x[, 2] >= x[, 1], 2]
if (length(realvalues) == 0)
warning("No observed x, estimation will not work.")
if (length(pqlvalues) == 0)
message("note: There is no censored data, estimation will proceed.",
"\n")
if (length(pqlvalues) > 0 & length(realvalues) > 0)
warning("cen and uncen present, fix0201.obs will not work")
N <- nrow(x)
m.little <- length(realvalues)
n.little <- length(pqlvalues)
u <- mean(x[, 1])
s <- sqrt(var(x[, 1]))
if (s == 0) {
stop("error fix0201.obs - all data are the same value = ",
u)
}
for (k in 1:iter) {
real.z <- (realvalues - u)/s
gam.wt <- (alpha + 0.5)/(beta + 0.5 * real.z^2)
real.wt <- sum(realvalues * gam.wt)
marg.wt <- sum(gam.wt)
newmu <- real.wt/marg.wt
real.ss <- sum((realvalues - newmu)^2 * gam.wt)
newsig <- sqrt((real.ss)/N)
eps <- sum(abs(c(u - newmu, s - newsig)))
iterno <- k
u <- newmu
s <- newsig
if (eps < converge)
break
}
real.z <- (realvalues - u)/s
psi <- sum((real.z * g1.m.singly.censored(real.z, 1.5, alpha,
beta))/g1.m.singly.censored(real.z, 0.5, alpha, beta))
chi <- sum(((real.z^2) * g1.m.singly.censored(real.z, 1.5,
alpha, beta))/g1.m.singly.censored(real.z, 0.5, alpha,
beta)) - m.little
labl <- c("maxiter", "iter", "u estim", "s estim", "psi~0",
"chi~0")
mestimate <- matrix(c(iter, iterno, u, s, psi, chi), 1, 6,
dimnames = list(iter, labl[1:6]))
if (iterno == iter)
message("no convergence ", "psi = ", psi, "chi = ", chi,
"\n")
consistent <- fix0111(d = x[1, 2], alpha = alpha, beta = beta,
mu = u, sigma = s, eta = u, kappa = s)
conestimate <- c(eta = consistent[1], kappa = consistent[3],
exp.psi = consistent[2], exp.chi = consistent[4])
list(mestimate = mestimate, conestimate = conestimate)
}
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