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gencalib<-function (Xs, Zs, d, total, q = rep(1, length(d)), method = c("linear",
"raking", "truncated", "logit"), bounds = c(low = 0, upp = 10),
description = FALSE, max_iter = 500, C = 1)
{
if (any(is.na(Xs)) | any(is.na(Zs)) | any(is.na(d)) | any(is.na(total)) |
any(is.na(q)))
stop("the input should not contain NAs")
if (!(is.matrix(Xs) | is.array(Xs)))
Xs = as.matrix(Xs)
if (is.matrix(Xs))
if (length(total) != ncol(Xs))
stop("Xs and total have different dimensions")
if (is.vector(Xs) & length(total) != 1)
stop("Xs and total have different dimensions")
if (!(is.matrix(Zs) | is.array(Zs)))
Zs = as.matrix(Zs)
if (any(dim(Xs) != dim(Zs)))
stop("Xs and Zs have different dimensions")
if (any(is.infinite(q)))
stop("there are Inf values in the q vector")
if (missing(method))
stop("Specify a method")
if (!(method %in% c("linear", "raking", "logit", "truncated")))
stop("the specified method is not in the list")
if (method %in% c("linear", "raking") & !missing(bounds))
stop("for the linear and raking the bounds are not allowed")
EPS = .Machine$double.eps
EPS1 = 1e-06
n = length(d)
lambda = as.matrix(rep(0, n))
lambda1 = ginv(t(Xs * d * q) %*% Zs, tol = EPS) %*% (total -
c(t(d) %*% Xs))
if (method == "linear" | max(abs(lambda1)) < EPS)
{g = 1 + q * c(Zs %*% lambda1) ; der = q}
else if (method == "truncated") {
if (!missing(bounds)) {
if (bounds[2] <= C || bounds[1] >= C || bounds[1] >
bounds[2])
stop("The conditions low<C<upp are not fulfilled")
}
else if (missing(bounds))
stop("Give the bounds")
g = 1 + q * c(Zs %*% lambda1)
der = q
list = 1:length(g)
l = 0
g1 = g
Xs1 = Xs
Zs1 = Zs
d1 = d
t2 = total
list1 = 1:length(g)
q1 = q
while (l < max_iter) {
l = l + 1
if (any(g < bounds[1]) | any(g > bounds[2])) {
g[g < bounds[1]] = bounds[1]
g[g > bounds[2]] = bounds[2]
list = (1:length(g))[g > bounds[1] & g < bounds[2]]
if (length(list) != 0) {
g1 = g[list]
t2 = total - c(t(g[-list] * d[-list]) %*% Xs[-list,
])
Xs1 = Xs[list, ]
Zs1 = Zs[list, ]
d1 = d[list]
q1 = q[list]
list1 = list
}
}
t1 = c(t(d1) %*% Xs1)
lambda1 = ginv(t(Xs1 * d1 * q1) %*% Zs1, tol = EPS) %*%
(t2 - t1)
if (length(list1) > 1)
g1 = 1 + q1 * c(Zs1 %*% lambda1)
else if (length(list1) == 1) {
g1 = 1 + q1 * c(as.vector(Zs1) %*% as.vector(lambda1))
}
g[list1] = g1
tr = crossprod(Xs, g * d)
expression = max(abs(tr - total)/total)
if(any(total==0)) expression = max(abs(tr - total))
if (expression < EPS1 & all(g >=
bounds[1] & g <= bounds[2]))
break
}
if (l == max_iter) {
cat("No convergence in", max_iter, "iterations with the given bounds. \n")
cat("The bounds for the g-weights are:", min(g),
" and ", max(g), "\n")
g=NULL
}
}
else if (method == "raking") {
lambda = as.matrix(rep(0, ncol(Xs)))
w1 = as.vector(d * exp(Zs %*% lambda * q))
T = t(Xs)
for (l in 1:max_iter) {
phi = t(Xs) %*% w1 - total
T1 = t(Xs * w1)
phiprim = T1 %*% Zs
lambda = lambda - ginv(phiprim, tol = EPS) %*% phi
w1 = as.vector(d * exp(Zs %*% lambda * q))
if (any(is.na(w1)) | any(is.infinite(w1)) | any(is.nan(w1))) {
warning("No convergence")
g = NULL
der = g
l = max_iter
break
}
tr = crossprod(Xs, w1)
expression = max(abs(tr - total)/total)
if(any(total==0)) expression = max(abs(tr - total))
if (expression < EPS1)
break
}
if (l == max_iter) {
warning("No convergence")
g = NULL
der = g
}
else {g = w1/d; der=g}
}
else if (method == "logit")
if (missing(bounds))
stop("Specify the bounds")
else
{
if (bounds[2] <= C || bounds[1] >= C || bounds[1] > bounds[2])
stop("The conditions low<C<upp are not fulfilled")
A = (bounds[2] - bounds[1])/((C - bounds[1]) * (bounds[2] - C))
u = rep(1, length(d))
F = (bounds[1] * (bounds[2] - C) + bounds[2] * (C - bounds[1]) *
u)/(bounds[2] - C + (C - bounds[1]) * u)
w1 = as.vector(d * F)
T = t(Xs * w1)
phiprim = ginv(T %*% Zs, tol = EPS)
g = F
tr = crossprod(Xs, w1)
expression = max(abs(tr - total)/total)
if(any(total==0)) expression = max(abs(tr - total))
if (expression > EPS1 | any(g < bounds[1]) |
any(g > bounds[2])) {
lambda1 = rep(0, ncol(Xs))
list = 1:length(g)
t2 = total
Xs1 = Xs
d1 = d
Zs1 = Zs
g1 = g
q1 = q
list1 = 1:length(g)
for (l in 1:max_iter) {
if (any(g < bounds[1]) | any(g > bounds[2])) {
g[g < bounds[1]] = bounds[1]
g[g > bounds[2]] = bounds[2]
list = (1:length(g))[g > bounds[1] & g < bounds[2]]
if (length(list) != 0) {
g1 = g[list]
t2 = total - c(t(g[-list] * d[-list]) %*%
Xs[-list, ])
Xs1 = Xs[list, ]
Zs1 = Zs[list, ]
d1 = d[list]
q1 = q[list]
list1 = list
}
else break
}
if (is.vector(Xs1)) {
warning("no convergence")
g1 = g = NULL
break
}
t1 = c(t(d1) %*% Xs1)
phi = t(Xs1) %*% as.vector(d1 * g1)
T = t(Xs1 * as.vector(d1 * g1))
phiprime = T %*% Zs1
lambda1 = lambda1 - ginv(phiprime, tol = EPS) %*%
(as.vector(phi) - t2)
u = exp(A * (Zs1 %*% lambda1 * q1))
F = g1 = (bounds[1] * (bounds[2] - C) + bounds[2] *
(C - bounds[1]) * u)/(bounds[2] - C + (C -
bounds[1]) * u)
if (any(is.na(g1))) {
warning("no convergence")
g1 = g = NULL
break
}
g[list1] = g1
der = g-1
tr = crossprod(Xs, g * d)
expression = max(abs(tr - total)/total)
if(any(total==0)) expression = max(abs(tr - total))
if (expression < EPS1 & all(g >=
bounds[1] & g <= bounds[2]))
break
}
if (l == max_iter) {
cat("no convergence in", max_iter, "iterations with the given bounds. \n")
cat("the bounds for the g-weights are:", min(g),
" and ", max(g), "\n")
cat(" and the g-weights are given by g\n")
g = NULL
der = g
}
}
}
if (description && !is.null(g)) {
par(mfrow = c(3, 2), pty = "s")
hist(g)
boxplot(g, main = "Boxplot of g")
hist(d)
boxplot(d, main = "Boxplot of d")
hist(g * d)
boxplot(g * d, main = "Boxplot of w=g*d")
if (method %in% c("truncated", "raking", "logit"))
cat("number of iterations ", l, "\n")
cat("summary - initial weigths d\n")
print(summary(d))
cat("summary - final weigths w=g*d\n")
print(summary(as.vector(g * d)))
}
g
}
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