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R/WeightsCalDF.R
In Frames2: Estimation in Dual Frame Surveys
#' @name WeightsCalDF
#' @aliases WeightsCalDF
#' @title g-weights for the dual frame calibration estimator
#'
#' @description Computes the g-weights for the dual frame calibration estimator.
#'
#' @usage WeightsCalDF(ysA, ysB, pi_A, pi_B, domains_A, domains_B, N_A = NULL, N_B = NULL,
#' N_ab = NULL, xsAFrameA = NULL, xsBFrameA = NULL, xsAFrameB = NULL, xsBFrameB = NULL,
#' xsT = NULL, XA = NULL, XB = NULL, X = NULL, met = "linear")
#' @param ysA A numeric vector of length \eqn{n_A} or a numeric matrix or data frame of dimensions \eqn{n_A} x \eqn{c} containing information about variable(s) of interest from \eqn{s_A}.
#' @param ysB A numeric vector of length \eqn{n_B} or a numeric matrix or data frame of dimensions \eqn{n_B} x \eqn{c} containing information about variable(s) of interest from \eqn{s_B}.
#' @param pi_A A numeric vector of length \eqn{n_A} or a square numeric matrix of dimension \eqn{n_A} containing first order or first and second order inclusion probabilities for units included in \eqn{s_A}.
#' @param pi_B A numeric vector of length \eqn{n_B} or a square numeric matrix of dimension \eqn{n_B} containing first order or first and second order inclusion probabilities for units included in \eqn{s_B}.
#' @param domains_A A character vector of length \eqn{n_A} indicating the domain each unit from \eqn{s_A} belongs to. Possible values are "a" and "ab".
#' @param domains_B A character vector of length \eqn{n_B} indicating the domain each unit from \eqn{s_B} belongs to. Possible values are "b" and "ba".
#' @param N_A (Optional) A numeric value indicating the size of frame A.
#' @param N_B (Optional) A numeric value indicating the size of frame B.
#' @param N_ab (Optional) A numeric value indicating the size of the overlap domain.
#' @param xsAFrameA (Optional) A numeric vector of length \eqn{n_A} or a numeric matrix or data frame of dimensions \eqn{n_A} x \eqn{m_A}, with \eqn{m_A} the number of auxiliary variables in frame A, containing auxiliary information in frame A for units included in \eqn{s_A}.
#' @param xsBFrameA (Optional) A numeric vector of length \eqn{n_B} or a numeric matrix or data frame of dimensions \eqn{n_B} x \eqn{m_A}, with \eqn{m_A} the number of auxiliary variables in frame A, containing auxiliary information in frame A for units included in \eqn{s_B}. For units in domain \eqn{b}, these values are 0.
#' @param xsAFrameB (Optional) A numeric vector of length \eqn{n_A} or a numeric matrix or data frame of dimensions \eqn{n_A} x \eqn{m_B}, with \eqn{m_B} the number of auxiliary variables in frame B, containing auxiliary information in frame B for units included in \eqn{s_A}. For units in domain \eqn{a}, these values are 0.
#' @param xsBFrameB (Optional) A numeric vector of length \eqn{n_B} or a numeric matrix or data frame of dimensions \eqn{n_B} x \eqn{m_B}, with \eqn{m_B} the number of auxiliary variables in frame B, containing auxiliary information in frame B for units included in \eqn{s_B}.
#' @param xsT (Optional) A numeric vector of length \eqn{n} or a numeric matrix or data frame of dimensions \eqn{n} x \eqn{m_T}, with \eqn{m_T} the number of auxiliary variables in both frames, containing auxiliary information for all units in the entire sample \eqn{s = s_A \cup s_B}.
#' @param XA (Optional) A numeric value or vector of length \eqn{m_A}, with \eqn{m_A} the number of auxiliary variables in frame A, indicating the population totals for the auxiliary variables considered in frame A.
#' @param XB (Optional) A numeric value or vector of length \eqn{m_B}, with \eqn{m_B} the number of auxiliary variables in frame B, indicating the population totals for the auxiliary variables considered in frame B.
#' @param X (Optional) A numeric value or vector of length \eqn{m_T}, with \eqn{m_T} the number of auxiliary variables in both frames, indicating the population totals for the auxiliary variables considered in both frames.
#' @param met (Optional) A character vector indicating the distance that must be used in calibration process. Possible values are "linear", "raking" and "logit". Default is "linear".
#' @details Function provides g-weights in following scenarios:
#' \itemize{
#' \item There is not any additional auxiliary variable
#' \itemize{
#' \item \eqn{N_A, N_B} and \eqn{N_{ab}} unknown
#' \item \eqn{N_{ab}} known and \eqn{N_A} and \eqn{N_B} unknown
#' \item \eqn{N_A} and \eqn{N_B} known and \eqn{N_{ab}} unknown
#' \item \eqn{N_A, N_B} and \eqn{N_{ab}} known
#' }
#' \item At least, one additional auxiliary variable is available
#' \itemize{
#' \item \eqn{N_{ab}} known and \eqn{N_A} and \eqn{N_B} unknown
#' \item \eqn{N_A} and \eqn{N_B} known and \eqn{N_{ab}} unknown
#' \item \eqn{N_A, N_B} and \eqn{N_{ab}} known
#' }
#' }
#' @return A numeric vector containing the g-weights for the dual frame calibration estimator.
#' @references Ranalli, M. G., Arcos, A., Rueda, M. and Teodoro, A. (2013)
#' \emph{Calibration estimationn in dual frame surveys}. arXiv:1312.0761 [stat.ME]
#' @references Deville, J. C., S\"arndal, C. E. (1992)
#' \emph{Calibration estimators in survey sampling.}
#' Journal of the American Statistical Association, 87, 376 - 382
#' @examples
#' data(DatA)
#' data(DatB)
#' data(PiklA)
#' data(PiklB)
#'
#' #Let calculate g-weights for the dual frame calibration estimator for variable Feeding,
#' #without considering any auxiliary information
#' WeightsCalDF(DatA$Feed, DatB$Feed, PiklA, PiklB, DatA$Domain, DatB$Domain)
#'
#' #Now, let calculate g-weights for the dual frame calibration estimator for variable Clothing
#' #when the frame sizes and the overlap domain size are known
#' WeightsCalDF(DatA$Clo, DatB$Clo, PiklA, PiklB, DatA$Domain, DatB$Domain,
#' N_A = 1735, N_B = 1191, N_ab = 601)
#'
#' #Finally, let calculate g-weights for the dual frame calibration estimator
#' #for variable Feeding, considering Income as auxiliary variable in frame A
#' #and Metres2 as auxiliary variable in frame B and with frame sizes and overlap
#' #domain size known.
#' WeightsCalDF(DatA$Feed, DatB$Feed, PiklA, PiklB, DatA$Domain, DatB$Domain,
#' N_A = 1735, N_B = 1191, N_ab = 601, xsAFrameA = DatA$Inc, xsBFrameA = DatB$Inc,
#' xsAFrameB = DatA$M2, xsBFrameB = DatB$M2, XA = 4300260, XB = 176553)
#' @export
WeightsCalDF = function (ysA, ysB, pi_A, pi_B, domains_A, domains_B, N_A = NULL, N_B = NULL, N_ab = NULL, xsAFrameA = NULL, xsBFrameA = NULL, xsAFrameB = NULL, xsBFrameB = NULL, xsT = NULL, XA = NULL, XB = NULL, X = NULL, met = "linear") {
cnames <- names(ysA)
ysA <- as.matrix(ysA)
ysB <- as.matrix(ysB)
pi_A <- as.matrix(pi_A)
pi_B <- as.matrix(pi_B)
if (any(is.na(ysA)))
stop("There are missing values in sample from frame A.")
if (any(is.na(ysB)))
stop("There are missing values in sample from frame B.")
if (any(is.na(pi_A)))
stop("There are missing values in pikl from frame A.")
if (any(is.na(pi_B)))
stop("There are missing values in pikl from frame B.")
if (any(is.na(domains_A)))
stop("There are missing values in domains from frame A.")
if (any(is.na(domains_B)))
stop("There are missing values in domains from frame B.")
if (nrow(ysA) != nrow(pi_A) | nrow(ysA) != length(domains_A) | length(domains_A) != nrow(pi_A))
stop("Arguments from frame A have different sizes.")
if (nrow(ysB) != nrow(pi_B) | nrow(ysB) != length(domains_B) | length(domains_B) != nrow(pi_B))
stop("Arguments from frame B have different sizes.")
if (length(which(domains_A == "a")) + length(which(domains_A == "ab")) != length(domains_A))
stop("Domains from frame A are not correct.")
if (length(which(domains_B == "b")) + length(which(domains_B == "ba")) != length(domains_B))
stop("Domains from frame B are not correct.")
if ((is.null (N_A) & !is.null (N_B)) | (!is.null (N_A) & is.null (N_B)))
stop("Only one value has been indicated for N_A and N_B. This is not valid. Both or none should be indicated.")
if (!is.null (N_ab) & (is.null (N_A) | is.null (N_B)))
stop("A value for N_ab has been provided, but values for N_A or N_B are missing. This is not a possible option.")
if ((is.null (xsAFrameA) & !is.null (xsBFrameA)) | (!is.null (xsAFrameA) & is.null (xsBFrameA)))
stop("Auxiliary information from Frame A is available only in one sample. This is not a possible option.")
if ((is.null (xsAFrameB) & !is.null (xsBFrameB)) | (!is.null (xsAFrameB) & is.null (xsBFrameB)))
stop("Auxiliary information from Frame B is available only in one sample. This is not a possible option.")
sample <- rbind(ysA, ysB)
domains <- factor(c(as.character(domains_A), as.character(domains_B)))
n_A <- nrow(ysA)
n_B <- nrow(ysB)
n <- n_A + n_B
c <- ncol(sample)
delta_a <- Domains (rep (1, n), domains, "a")
delta_ab <- Domains (rep (1, n), domains, "ab")
delta_b <- Domains (rep (1, n), domains, "b")
delta_ba <- Domains (rep (1, n), domains, "ba")
ones_a_A <- Domains (rep (1, n_A), domains_A, "a")
ones_ab_A <- Domains (rep (1, n_A), domains_A, "ab")
ones_b_B <- Domains (rep (1, n_B), domains_B, "b")
ones_ab_B <- Domains (rep (1, n_B), domains_B, "ba")
results <- matrix(NA, nrow = n, ncol = c)
colnames (results) <- cnames
if (!is.null(dim(drop(pi_A))) & !is.null(dim(drop(pi_B)))) {
if (nrow(pi_A) != ncol(pi_A))
stop("Pikl from frame A is not a square matrix.")
if (nrow(pi_B) != ncol(pi_B))
stop("Pikl from frame B is not a square matrix.")
pik <- c(diag(pi_A), diag(pi_B))
dd <- 1/pik
Nhat_a_A <- HT (ones_a_A, diag(pi_A))
Nhat_ab_A <- HT (ones_ab_A, diag(pi_A))
Nhat_b_B <- HT (ones_b_B, diag(pi_B))
Nhat_ab_B <- HT (ones_ab_B, diag(pi_B))
Vhat_Nhat_ab_A <- VarHT(ones_ab_A, pi_A)
Vhat_Nhat_ab_B <- VarHT(ones_ab_B, pi_B)
eta_0 <- Vhat_Nhat_ab_B / (Vhat_Nhat_ab_A + Vhat_Nhat_ab_B)
for (k in 1:c) {
d <- dd*delta_a + dd*eta_0*delta_ab + dd*(1-eta_0)*delta_ba + dd*delta_b
if (is.null(xsAFrameA) & is.null(xsBFrameB) & is.null(xsT)) {
if (is.null(N_ab)) {
if (is.null(N_A) & is.null(N_B)) {
Nhat_abP <- eta_0 * Nhat_ab_A + (1 - eta_0) * Nhat_ab_B
Nhat_A <- HT (ones_a_A + ones_ab_A, diag(pi_A))
Nhat_B <- HT (ones_b_B + ones_ab_B, diag(pi_B))
Xs <- cbind(delta_a, delta_ab, delta_ba, delta_b)
total <- c(Nhat_A - Nhat_abP, eta_0 * Nhat_abP, (1 - eta_0) * Nhat_abP, Nhat_B - Nhat_abP)
}
else {
Xs <- cbind(delta_a + delta_ab + delta_ba, delta_b + delta_ab + delta_ba)
total <- c(N_A, N_B)
}
}
else {
if (is.null(N_A) & is.null(N_B)) {
Xs <- cbind(delta_ab, delta_ba)
total <- c(eta_0 * N_ab, (1 - eta_0) * N_ab)
}else {
Xs <- cbind(delta_a, delta_ab, delta_ba, delta_b)
total <- c(N_A - N_ab, eta_0 * N_ab, (1 - eta_0) * N_ab, N_B - N_ab)
}
}
}
else {
if (is.null(N_ab)) {
if (is.null(xsAFrameA)){
if (is.null(xsBFrameB)){
xsT <- as.matrix(xsT)
Xs <- cbind(delta_a + delta_ab + delta_ba, delta_b + delta_ab + delta_ba, (delta_a + delta_ab + delta_b + delta_ba) * xsT)
total <- c(N_A, N_B, X)
}
else {
xsAFrameB <- as.matrix(xsAFrameB); xsBFrameB <- as.matrix(xsBFrameB)
XFrameB <- rbind(xsAFrameB, xsBFrameB)
if (is.null(xsT)){
Xs <- cbind(delta_a + delta_ab + delta_ba, delta_b + delta_ab + delta_ba, (delta_b + delta_ab + delta_ba) * XFrameB)
total <- c(N_A, N_B, XB)
}
else {
xsT <- as.matrix(xsT)
Xs <- cbind(delta_a + delta_ab + delta_ba, delta_b + delta_ab + delta_ba, (delta_b + delta_ab + delta_ba) * XFrameB, (delta_a + delta_ab + delta_b + delta_ba) * xsT)
total <- c(N_A, N_B, XB, X)
}
}
}
else {
xsAFrameA <- as.matrix(xsAFrameA); xsBFrameA <- as.matrix(xsBFrameA)
XFrameA <- rbind(xsAFrameA, xsBFrameA)
if (is.null(xsBFrameB)){
if (is.null(xsT)){
Xs <- cbind(delta_a + delta_ab + delta_ba, delta_b + delta_ab + delta_ba, (delta_a + delta_ab + delta_ba) * XFrameA)
total <- c(N_A, N_B, XA)
}
else{
xsT <- as.matrix(xsT)
Xs <- cbind(delta_a + delta_ab + delta_ba, delta_b + delta_ab + delta_ba, (delta_a + delta_ab + delta_ba) * XFrameA, (delta_a + delta_ab + delta_b + delta_ba) * xsT)
total <- c(N_A, N_B, XA, X)
}
}
else{
xsAFrameB <- as.matrix(xsAFrameB); xsBFrameB <- as.matrix(xsBFrameB)
XFrameB <- rbind(xsAFrameB, xsBFrameB)
if (is.null(xsT)){
Xs <- cbind(delta_a + delta_ab + delta_ba, delta_b + delta_ab + delta_ba, (delta_a + delta_ab + delta_ba) * XFrameA, (delta_b + delta_ab + delta_ba) * XFrameB)
total <- c(N_A, N_B, XA, XB)
}
else{
xsT <- as.matrix(xsT)
Xs <- Xs <- cbind(delta_a + delta_ab + delta_ba, delta_b + delta_ab + delta_ba, (delta_a + delta_ab + delta_ba) * XFrameA, (delta_b + delta_ab + delta_ba) * XFrameB, (delta_a + delta_ab + delta_b + delta_ba) * xsT)
total <- c(N_A, N_B, XA, XB, X)
}
}
}
}
else {
if (is.null(N_A) & is.null(N_B)) {
if (is.null(xsAFrameA)){
if (is.null(xsBFrameB)){
xsT <- as.matrix(xsT)
Xs <- cbind(delta_ab, delta_ba, xsT)
total <- c(eta_0 * N_ab, (1 - eta_0) * N_ab, X)
}
else {
xsAFrameB <- as.matrix(xsAFrameB); xsBFrameB <- as.matrix(xsBFrameB)
XFrameB <- rbind(xsAFrameB, xsBFrameB)
if (is.null(xsT)){
Xs <- cbind(delta_ab, delta_ba, (delta_b + delta_ab + delta_ba) * XFrameB)
total <- c(eta_0 * N_ab, (1 - eta_0) * N_ab, XB)
}
else {
xsT <- as.matrix(xsT)
Xs <- cbind(delta_ab, delta_ba, (delta_b + delta_ab + delta_ba) * XFrameB, (delta_a + delta_ab + delta_b + delta_ba) * xsT)
total <- c(eta_0 * N_ab, (1 - eta_0) * N_ab, XB, X)
}
}
}
else {
xsAFrameA <- as.matrix(xsAFrameA); xsBFrameA <- as.matrix(xsBFrameA)
XFrameA <- rbind(xsAFrameA, xsBFrameA)
if (is.null(xsBFrameB)){
if (is.null(xsT)){
Xs <- cbind(delta_ab, delta_ba, (delta_a + delta_ab + delta_ba) * XFrameA)
total <- c(eta_0 * N_ab, (1 - eta_0) * N_ab, XA)
}
else{
xsT <- as.matrix(xsT)
Xs <- cbind(delta_ab, delta_ba, (delta_a + delta_ab + delta_ba) * XFrameA, (delta_a + delta_ab + delta_b + delta_ba) * xsT)
total <- c(eta_0 * N_ab, (1 - eta_0) * N_ab, XA, X)
}
}
else{
xsAFrameB <- as.matrix(xsAFrameB); xsBFrameB <- as.matrix(xsBFrameB)
XFrameB <- rbind(xsAFrameB, xsBFrameB)
if (is.null(xsT)){
Xs <- cbind(delta_ab, delta_ba, (delta_a + delta_ab + delta_ba) * XFrameA, (delta_b + delta_ab + delta_ba) * XFrameB)
total <- c(eta_0 * N_ab, (1 - eta_0) * N_ab, XA, XB)
}
else{
xsT <- as.matrix(xsT)
Xs <- cbind(delta_ab, delta_ba, (delta_a + delta_ab + delta_ba) * XFrameA, (delta_b + delta_ab + delta_ba) * XFrameB, (delta_a + delta_ab + delta_b + delta_ba) * xsT)
total <- c(eta_0 * N_ab, (1 - eta_0) * N_ab, XA, XB, X)
}
}
}
}
else {
if (is.null(xsAFrameA)){
if (is.null(xsBFrameB)){
xsT <- as.matrix(xsT)
Xs <- cbind(delta_a, delta_ab, delta_b, delta_ba, xsT)
total <- c(N_A - N_ab, eta_0 * N_ab, N_B - N_ab, (1 - eta_0) * N_ab, X)
}
else {
xsAFrameB <- as.matrix(xsAFrameB); xsBFrameB <- as.matrix(xsBFrameB)
XFrameB <- rbind(xsAFrameB, xsBFrameB)
if (is.null(xsT)){
Xs <- cbind(delta_a, delta_ab, delta_b, delta_ba, (delta_b + delta_ab + delta_ba) * XFrameB)
total <- c(N_A - N_ab, eta_0 * N_ab, N_B - N_ab, (1 - eta_0) * N_ab, XB)
}
else {
xsT <- as.matrix(xsT)
Xs <- cbind(delta_a, delta_ab, delta_b, delta_ba, (delta_b + delta_ab + delta_ba) * XFrameB, (delta_a + delta_ab + delta_b + delta_ba) * xsT)
total <- c(N_A - N_ab, eta_0 * N_ab, N_B - N_ab, (1 - eta_0) * N_ab, XB, X)
}
}
}
else {
xsAFrameA <- as.matrix(xsAFrameA); xsBFrameA <- as.matrix(xsBFrameA)
XFrameA <- rbind(xsAFrameA, xsBFrameA)
if (is.null(xsBFrameB)){
if (is.null(xsT)){
Xs <- cbind(delta_a, delta_ab, delta_b, delta_ba, (delta_a + delta_ab + delta_ba) * XFrameA)
total <- c(N_A - N_ab, eta_0 * N_ab, N_B - N_ab, (1 - eta_0) * N_ab, XA)
}
else{
xsT <- as.matrix(xsT)
Xs <- cbind(delta_a, delta_ab, delta_b, delta_ba, (delta_a + delta_ab + delta_ba) * XFrameA, (delta_a + delta_ab + delta_b + delta_ba) * xsT)
total <- c(N_A - N_ab, eta_0 * N_ab, N_B - N_ab, (1 - eta_0) * N_ab, XA, X)
}
}
else{
xsAFrameB <- as.matrix(xsAFrameB); xsBFrameB <- as.matrix(xsBFrameB)
XFrameB <- rbind(xsAFrameB, xsBFrameB)
if (is.null(xsT)){
Xs <- cbind(delta_a, delta_ab, delta_b, delta_ba, (delta_a + delta_ab + delta_ba) * XFrameA, (delta_b + delta_ab + delta_ba) * XFrameB)
total <- c(N_A - N_ab, eta_0 * N_ab, N_B - N_ab, (1 - eta_0) * N_ab, XA, XB)
}
else{
xsT <- as.matrix(xsT)
Xs <- cbind(delta_a, delta_ab, delta_b, delta_ba, (delta_a + delta_ab + delta_ba) * XFrameA, (delta_b + delta_ab + delta_ba) * XFrameB, (delta_a + delta_ab + delta_b + delta_ba) * xsT)
total <- c(N_A - N_ab, eta_0 * N_ab, N_B - N_ab, (1 - eta_0) * N_ab, XA, XB, X)
}
}
}
}
}
}
results[,k] <- calib (Xs, d, total, method = met)
}
}
else {
if (is.null(dim(drop(pi_A))) & is.null(dim(drop(pi_B)))){
pik <- c(pi_A, pi_B)
dd <- 1/pik
Nhat_a_A <- HT (ones_a_A, pi_A)
Nhat_ab_A <- HT (ones_ab_A, pi_A)
Nhat_b_B <- HT (ones_b_B, pi_B)
Nhat_ab_B <- HT (ones_ab_B, pi_B)
Vhat_Nhat_ab_A <- varest(ones_ab_A, pik = pi_A)
Vhat_Nhat_ab_B <- varest(ones_ab_B, pik = pi_B)
eta_0 <- Vhat_Nhat_ab_B / (Vhat_Nhat_ab_A + Vhat_Nhat_ab_B)
for (k in 1:ncol(sample)) {
d <- dd*delta_a + dd*eta_0*delta_ab + dd*(1-eta_0)*delta_ba + dd*delta_b
if (is.null(xsAFrameA) & is.null(xsBFrameB) & is.null(xsT)) {
if (is.null(N_ab)) {
if (is.null(N_A) & is.null(N_B)) {
Nhat_abP <- eta_0 * Nhat_ab_A + (1 - eta_0) * Nhat_ab_B
Nhat_A <- HT (ones_a_A + ones_ab_A, pi_A)
Nhat_B <- HT (ones_b_B + ones_ab_B, pi_B)
Xs <- cbind(delta_a, delta_ab, delta_ba, delta_b)
total <- c(Nhat_A - Nhat_abP, eta_0 * Nhat_abP, (1 - eta_0) * Nhat_abP, Nhat_B - Nhat_abP)
}
else {
Xs <- cbind(delta_a + delta_ab + delta_ba, delta_b + delta_ab + delta_ba)
total <- c(N_A, N_B)
}
}
else {
if (is.null(N_A) & is.null(N_B)) {
Xs <- cbind(delta_ab, delta_ba)
total <- c(eta_0 * N_ab, (1 - eta_0) * N_ab)
}
else {
Xs <- cbind(delta_a, delta_ab, delta_ba, delta_b)
total <- c(N_A - N_ab, eta_0 * N_ab, (1 - eta_0) * N_ab, N_B - N_ab)
}
}
}
else {
if (is.null(N_ab)) {
if (is.null(xsAFrameA)){
if (is.null(xsBFrameB)){
xsT <- as.matrix(xsT)
Xs <- cbind(delta_a + delta_ab + delta_ba, delta_b + delta_ab + delta_ba, (delta_a + delta_ab + delta_b + delta_ba) * xsT)
total <- c(N_A, N_B, X)
}
else {
xsAFrameB <- as.matrix(xsAFrameB); xsBFrameB <- as.matrix(xsBFrameB)
XFrameB <- rbind(xsAFrameB, xsBFrameB)
if (is.null(xsT)){
Xs <- cbind(delta_a + delta_ab + delta_ba, delta_b + delta_ab + delta_ba, (delta_b + delta_ab + delta_ba) * XFrameB)
total <- c(N_A, N_B, XB)
}
else {
xsT <- as.matrix(xsT)
Xs <- cbind(delta_a + delta_ab + delta_ba, delta_b + delta_ab + delta_ba, (delta_b + delta_ab + delta_ba) * XFrameB, (delta_a + delta_ab + delta_b + delta_ba) * xsT)
total <- c(N_A, N_B, XB, X)
}
}
}
else {
xsAFrameA <- as.matrix(xsAFrameA); xsBFrameA <- as.matrix(xsBFrameA)
XFrameA <- rbind(xsAFrameA, xsBFrameA)
if (is.null(xsBFrameB)){
if (is.null(xsT)){
Xs <- cbind(delta_a + delta_ab + delta_ba, delta_b + delta_ab + delta_ba, (delta_a + delta_ab + delta_ba) * XFrameA)
total <- c(N_A, N_B, XA)
}
else{
xsT <- as.matrix(xsT)
Xs <- cbind(delta_a + delta_ab + delta_ba, delta_b + delta_ab + delta_ba, (delta_a + delta_ab + delta_ba) * XFrameA, (delta_a + delta_ab + delta_b + delta_ba) * xsT)
total <- c(N_A, N_B, XA, X)
}
}
else{
xsAFrameB <- as.matrix(xsAFrameB); xsBFrameB <- as.matrix(xsBFrameB)
XFrameB <- rbind(xsAFrameB, xsBFrameB)
if (is.null(xsT)){
Xs <- cbind(delta_a + delta_ab + delta_ba, delta_b + delta_ab + delta_ba, (delta_a + delta_ab + delta_ba) * XFrameA, (delta_b + delta_ab + delta_ba) * XFrameB)
total <- c(N_A, N_B, XA, XB)
}
else{
xsT <- as.matrix(xsT)
Xs <- Xs <- cbind(delta_a + delta_ab + delta_ba, delta_b + delta_ab + delta_ba, (delta_a + delta_ab + delta_ba) * XFrameA, (delta_b + delta_ab + delta_ba) * XFrameB, (delta_a + delta_ab + delta_b + delta_ba) * xsT)
total <- c(N_A, N_B, XA, XB, X)
}
}
}
}
else {
if (is.null(N_A) & is.null(N_B)) {
if (is.null(xsAFrameA)){
if (is.null(xsBFrameB)){
xsT <- as.matrix(xsT)
Xs <- cbind(delta_ab, delta_ba, xsT)
total <- c(eta_0 * N_ab, (1 - eta_0) * N_ab, X)
}
else {
xsAFrameB <- as.matrix(xsAFrameB); xsBFrameB <- as.matrix(xsBFrameB)
XFrameB <- rbind(xsAFrameB, xsBFrameB)
if (is.null(xsT)){
Xs <- cbind(delta_ab, delta_ba, (delta_b + delta_ab + delta_ba) * XFrameB)
total <- c(eta_0 * N_ab, (1 - eta_0) * N_ab, XB)
}
else {
xsT <- as.matrix(xsT)
Xs <- cbind(delta_ab, delta_ba, (delta_b + delta_ab + delta_ba) * XFrameB, (delta_a + delta_ab + delta_b + delta_ba) * xsT)
total <- c(eta_0 * N_ab, (1 - eta_0) * N_ab, XB, X)
}
}
}
else {
xsAFrameA <- as.matrix(xsAFrameA); xsBFrameA <- as.matrix(xsBFrameA)
XFrameA <- rbind(xsAFrameA, xsBFrameA)
if (is.null(xsBFrameB)){
if (is.null(xsT)){
Xs <- cbind(delta_ab, delta_ba, (delta_a + delta_ab + delta_ba) * XFrameA)
total <- c(eta_0 * N_ab, (1 - eta_0) * N_ab, XA)
}
else{
xsT <- as.matrix(xsT)
Xs <- cbind(delta_ab, delta_ba, (delta_a + delta_ab + delta_ba) * XFrameA, (delta_a + delta_ab + delta_b + delta_ba) * xsT)
total <- c(eta_0 * N_ab, (1 - eta_0) * N_ab, XA, X)
}
}
else{
xsAFrameB <- as.matrix(xsAFrameB); xsBFrameB <- as.matrix(xsBFrameB)
XFrameB <- rbind(xsAFrameB, xsBFrameB)
if (is.null(xsT)){
Xs <- cbind(delta_ab, delta_ba, (delta_a + delta_ab + delta_ba) * XFrameA, (delta_b + delta_ab + delta_ba) * XFrameB)
total <- c(eta_0 * N_ab, (1 - eta_0) * N_ab, XA, XB)
}
else{
xsT <- as.matrix(xsT)
Xs <- cbind(delta_ab, delta_ba, (delta_a + delta_ab + delta_ba) * XFrameA, (delta_b + delta_ab + delta_ba) * XFrameB, (delta_a + delta_ab + delta_b + delta_ba) * xsT)
total <- c(eta_0 * N_ab, (1 - eta_0) * N_ab, XA, XB, X)
}
}
}
}
else {
if (is.null(xsAFrameA)){
if (is.null(xsBFrameB)){
xsT <- as.matrix(xsT)
Xs <- cbind(delta_a, delta_ab, delta_b, delta_ba, xsT)
total <- c(N_A - N_ab, eta_0 * N_ab, N_B - N_ab, (1 - eta_0) * N_ab, X)
}
else {
xsAFrameB <- as.matrix(xsAFrameB); xsBFrameB <- as.matrix(xsBFrameB)
XFrameB <- rbind(xsAFrameB, xsBFrameB)
if (is.null(xsT)){
Xs <- cbind(delta_a, delta_ab, delta_b, delta_ba, (delta_b + delta_ab + delta_ba) * XFrameB)
total <- c(N_A - N_ab, eta_0 * N_ab, N_B - N_ab, (1 - eta_0) * N_ab, XB)
}
else {
xsT <- as.matrix(xsT)
Xs <- cbind(delta_a, delta_ab, delta_b, delta_ba, (delta_b + delta_ab + delta_ba) * XFrameB, (delta_a + delta_ab + delta_b + delta_ba) * xsT)
total <- c(N_A - N_ab, eta_0 * N_ab, N_B - N_ab, (1 - eta_0) * N_ab, XB, X)
}
}
}
else {
xsAFrameA <- as.matrix(xsAFrameA); xsBFrameA <- as.matrix(xsBFrameA)
XFrameA <- rbind(xsAFrameA, xsBFrameA)
if (is.null(xsBFrameB)){
if (is.null(xsT)){
Xs <- cbind(delta_a, delta_ab, delta_b, delta_ba, (delta_a + delta_ab + delta_ba) * XFrameA)
total <- c(N_A - N_ab, eta_0 * N_ab, N_B - N_ab, (1 - eta_0) * N_ab, XA)
}
else{
xsT <- as.matrix(xsT)
Xs <- cbind(delta_a, delta_ab, delta_b, delta_ba, (delta_a + delta_ab + delta_ba) * XFrameA, (delta_a + delta_ab + delta_b + delta_ba) * xsT)
total <- c(N_A - N_ab, eta_0 * N_ab, N_B - N_ab, (1 - eta_0) * N_ab, XA, X)
}
}
else{
xsAFrameB <- as.matrix(xsAFrameB); xsBFrameB <- as.matrix(xsBFrameB)
XFrameB <- rbind(xsAFrameB, xsBFrameB)
if (is.null(xsT)){
Xs <- cbind(delta_a, delta_ab, delta_b, delta_ba, (delta_a + delta_ab + delta_ba) * XFrameA, (delta_b + delta_ab + delta_ba) * XFrameB)
total <- c(N_A - N_ab, eta_0 * N_ab, N_B - N_ab, (1 - eta_0) * N_ab, XA, XB)
}
else{
xsT <- as.matrix(xsT)
Xs <- cbind(delta_a, delta_ab, delta_b, delta_ba, (delta_a + delta_ab + delta_ba) * XFrameA, (delta_b + delta_ab + delta_ba) * XFrameB, (delta_a + delta_ab + delta_b + delta_ba) * xsT)
total <- c(N_A - N_ab, eta_0 * N_ab, N_B - N_ab, (1 - eta_0) * N_ab, XA, XB, X)
}
}
}
}
}
}
results[,k] <- calib (Xs, d, total, method = met)
}
}
else
stop("Invalid option: Probability vector in one frame and probability matrix in the other frame. Type of both structures must match.")
}
return (results)
}
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#' @name WeightsCalDF
#' @aliases WeightsCalDF
#' @title g-weights for the dual frame calibration estimator
#'
#' @description Computes the g-weights for the dual frame calibration estimator.
#'
#' @usage WeightsCalDF(ysA, ysB, pi_A, pi_B, domains_A, domains_B, N_A = NULL, N_B = NULL,
#' N_ab = NULL, xsAFrameA = NULL, xsBFrameA = NULL, xsAFrameB = NULL, xsBFrameB = NULL,
#' xsT = NULL, XA = NULL, XB = NULL, X = NULL, met = "linear")
#' @param ysA A numeric vector of length \eqn{n_A} or a numeric matrix or data frame of dimensions \eqn{n_A} x \eqn{c} containing information about variable(s) of interest from \eqn{s_A}.
#' @param ysB A numeric vector of length \eqn{n_B} or a numeric matrix or data frame of dimensions \eqn{n_B} x \eqn{c} containing information about variable(s) of interest from \eqn{s_B}.
#' @param pi_A A numeric vector of length \eqn{n_A} or a square numeric matrix of dimension \eqn{n_A} containing first order or first and second order inclusion probabilities for units included in \eqn{s_A}.
#' @param pi_B A numeric vector of length \eqn{n_B} or a square numeric matrix of dimension \eqn{n_B} containing first order or first and second order inclusion probabilities for units included in \eqn{s_B}.
#' @param domains_A A character vector of length \eqn{n_A} indicating the domain each unit from \eqn{s_A} belongs to. Possible values are "a" and "ab".
#' @param domains_B A character vector of length \eqn{n_B} indicating the domain each unit from \eqn{s_B} belongs to. Possible values are "b" and "ba".
#' @param N_A (Optional) A numeric value indicating the size of frame A.
#' @param N_B (Optional) A numeric value indicating the size of frame B.
#' @param N_ab (Optional) A numeric value indicating the size of the overlap domain.
#' @param xsAFrameA (Optional) A numeric vector of length \eqn{n_A} or a numeric matrix or data frame of dimensions \eqn{n_A} x \eqn{m_A}, with \eqn{m_A} the number of auxiliary variables in frame A, containing auxiliary information in frame A for units included in \eqn{s_A}.
#' @param xsBFrameA (Optional) A numeric vector of length \eqn{n_B} or a numeric matrix or data frame of dimensions \eqn{n_B} x \eqn{m_A}, with \eqn{m_A} the number of auxiliary variables in frame A, containing auxiliary information in frame A for units included in \eqn{s_B}. For units in domain \eqn{b}, these values are 0.
#' @param xsAFrameB (Optional) A numeric vector of length \eqn{n_A} or a numeric matrix or data frame of dimensions \eqn{n_A} x \eqn{m_B}, with \eqn{m_B} the number of auxiliary variables in frame B, containing auxiliary information in frame B for units included in \eqn{s_A}. For units in domain \eqn{a}, these values are 0.
#' @param xsBFrameB (Optional) A numeric vector of length \eqn{n_B} or a numeric matrix or data frame of dimensions \eqn{n_B} x \eqn{m_B}, with \eqn{m_B} the number of auxiliary variables in frame B, containing auxiliary information in frame B for units included in \eqn{s_B}.
#' @param xsT (Optional) A numeric vector of length \eqn{n} or a numeric matrix or data frame of dimensions \eqn{n} x \eqn{m_T}, with \eqn{m_T} the number of auxiliary variables in both frames, containing auxiliary information for all units in the entire sample \eqn{s = s_A \cup s_B}.
#' @param XA (Optional) A numeric value or vector of length \eqn{m_A}, with \eqn{m_A} the number of auxiliary variables in frame A, indicating the population totals for the auxiliary variables considered in frame A.
#' @param XB (Optional) A numeric value or vector of length \eqn{m_B}, with \eqn{m_B} the number of auxiliary variables in frame B, indicating the population totals for the auxiliary variables considered in frame B.
#' @param X (Optional) A numeric value or vector of length \eqn{m_T}, with \eqn{m_T} the number of auxiliary variables in both frames, indicating the population totals for the auxiliary variables considered in both frames.
#' @param met (Optional) A character vector indicating the distance that must be used in calibration process. Possible values are "linear", "raking" and "logit". Default is "linear".
#' @details Function provides g-weights in following scenarios:
#' \itemize{
#' \item There is not any additional auxiliary variable
#' \itemize{
#' \item \eqn{N_A, N_B} and \eqn{N_{ab}} unknown
#' \item \eqn{N_{ab}} known and \eqn{N_A} and \eqn{N_B} unknown
#' \item \eqn{N_A} and \eqn{N_B} known and \eqn{N_{ab}} unknown
#' \item \eqn{N_A, N_B} and \eqn{N_{ab}} known
#' }
#' \item At least, one additional auxiliary variable is available
#' \itemize{
#' \item \eqn{N_{ab}} known and \eqn{N_A} and \eqn{N_B} unknown
#' \item \eqn{N_A} and \eqn{N_B} known and \eqn{N_{ab}} unknown
#' \item \eqn{N_A, N_B} and \eqn{N_{ab}} known
#' }
#' }
#' @return A numeric vector containing the g-weights for the dual frame calibration estimator.
#' @references Ranalli, M. G., Arcos, A., Rueda, M. and Teodoro, A. (2013)
#' \emph{Calibration estimationn in dual frame surveys}. arXiv:1312.0761 [stat.ME]
#' @references Deville, J. C., S\"arndal, C. E. (1992)
#' \emph{Calibration estimators in survey sampling.}
#' Journal of the American Statistical Association, 87, 376 - 382
#' @examples
#' data(DatA)
#' data(DatB)
#' data(PiklA)
#' data(PiklB)
#'
#' #Let calculate g-weights for the dual frame calibration estimator for variable Feeding,
#' #without considering any auxiliary information
#' WeightsCalDF(DatA$Feed, DatB$Feed, PiklA, PiklB, DatA$Domain, DatB$Domain)
#'
#' #Now, let calculate g-weights for the dual frame calibration estimator for variable Clothing
#' #when the frame sizes and the overlap domain size are known
#' WeightsCalDF(DatA$Clo, DatB$Clo, PiklA, PiklB, DatA$Domain, DatB$Domain,
#' N_A = 1735, N_B = 1191, N_ab = 601)
#'
#' #Finally, let calculate g-weights for the dual frame calibration estimator
#' #for variable Feeding, considering Income as auxiliary variable in frame A
#' #and Metres2 as auxiliary variable in frame B and with frame sizes and overlap
#' #domain size known.
#' WeightsCalDF(DatA$Feed, DatB$Feed, PiklA, PiklB, DatA$Domain, DatB$Domain,
#' N_A = 1735, N_B = 1191, N_ab = 601, xsAFrameA = DatA$Inc, xsBFrameA = DatB$Inc,
#' xsAFrameB = DatA$M2, xsBFrameB = DatB$M2, XA = 4300260, XB = 176553)
#' @export
WeightsCalDF = function (ysA, ysB, pi_A, pi_B, domains_A, domains_B, N_A = NULL, N_B = NULL, N_ab = NULL, xsAFrameA = NULL, xsBFrameA = NULL, xsAFrameB = NULL, xsBFrameB = NULL, xsT = NULL, XA = NULL, XB = NULL, X = NULL, met = "linear") {
cnames <- names(ysA)
ysA <- as.matrix(ysA)
ysB <- as.matrix(ysB)
pi_A <- as.matrix(pi_A)
pi_B <- as.matrix(pi_B)
if (any(is.na(ysA)))
stop("There are missing values in sample from frame A.")
if (any(is.na(ysB)))
stop("There are missing values in sample from frame B.")
if (any(is.na(pi_A)))
stop("There are missing values in pikl from frame A.")
if (any(is.na(pi_B)))
stop("There are missing values in pikl from frame B.")
if (any(is.na(domains_A)))
stop("There are missing values in domains from frame A.")
if (any(is.na(domains_B)))
stop("There are missing values in domains from frame B.")
if (nrow(ysA) != nrow(pi_A) | nrow(ysA) != length(domains_A) | length(domains_A) != nrow(pi_A))
stop("Arguments from frame A have different sizes.")
if (nrow(ysB) != nrow(pi_B) | nrow(ysB) != length(domains_B) | length(domains_B) != nrow(pi_B))
stop("Arguments from frame B have different sizes.")
if (length(which(domains_A == "a")) + length(which(domains_A == "ab")) != length(domains_A))
stop("Domains from frame A are not correct.")
if (length(which(domains_B == "b")) + length(which(domains_B == "ba")) != length(domains_B))
stop("Domains from frame B are not correct.")
if ((is.null (N_A) & !is.null (N_B)) | (!is.null (N_A) & is.null (N_B)))
stop("Only one value has been indicated for N_A and N_B. This is not valid. Both or none should be indicated.")
if (!is.null (N_ab) & (is.null (N_A) | is.null (N_B)))
stop("A value for N_ab has been provided, but values for N_A or N_B are missing. This is not a possible option.")
if ((is.null (xsAFrameA) & !is.null (xsBFrameA)) | (!is.null (xsAFrameA) & is.null (xsBFrameA)))
stop("Auxiliary information from Frame A is available only in one sample. This is not a possible option.")
if ((is.null (xsAFrameB) & !is.null (xsBFrameB)) | (!is.null (xsAFrameB) & is.null (xsBFrameB)))
stop("Auxiliary information from Frame B is available only in one sample. This is not a possible option.")
sample <- rbind(ysA, ysB)
domains <- factor(c(as.character(domains_A), as.character(domains_B)))
n_A <- nrow(ysA)
n_B <- nrow(ysB)
n <- n_A + n_B
c <- ncol(sample)
delta_a <- Domains (rep (1, n), domains, "a")
delta_ab <- Domains (rep (1, n), domains, "ab")
delta_b <- Domains (rep (1, n), domains, "b")
delta_ba <- Domains (rep (1, n), domains, "ba")
ones_a_A <- Domains (rep (1, n_A), domains_A, "a")
ones_ab_A <- Domains (rep (1, n_A), domains_A, "ab")
ones_b_B <- Domains (rep (1, n_B), domains_B, "b")
ones_ab_B <- Domains (rep (1, n_B), domains_B, "ba")
results <- matrix(NA, nrow = n, ncol = c)
colnames (results) <- cnames
if (!is.null(dim(drop(pi_A))) & !is.null(dim(drop(pi_B)))) {
if (nrow(pi_A) != ncol(pi_A))
stop("Pikl from frame A is not a square matrix.")
if (nrow(pi_B) != ncol(pi_B))
stop("Pikl from frame B is not a square matrix.")
pik <- c(diag(pi_A), diag(pi_B))
dd <- 1/pik
Nhat_a_A <- HT (ones_a_A, diag(pi_A))
Nhat_ab_A <- HT (ones_ab_A, diag(pi_A))
Nhat_b_B <- HT (ones_b_B, diag(pi_B))
Nhat_ab_B <- HT (ones_ab_B, diag(pi_B))
Vhat_Nhat_ab_A <- VarHT(ones_ab_A, pi_A)
Vhat_Nhat_ab_B <- VarHT(ones_ab_B, pi_B)
eta_0 <- Vhat_Nhat_ab_B / (Vhat_Nhat_ab_A + Vhat_Nhat_ab_B)
for (k in 1:c) {
d <- dd*delta_a + dd*eta_0*delta_ab + dd*(1-eta_0)*delta_ba + dd*delta_b
if (is.null(xsAFrameA) & is.null(xsBFrameB) & is.null(xsT)) {
if (is.null(N_ab)) {
if (is.null(N_A) & is.null(N_B)) {
Nhat_abP <- eta_0 * Nhat_ab_A + (1 - eta_0) * Nhat_ab_B
Nhat_A <- HT (ones_a_A + ones_ab_A, diag(pi_A))
Nhat_B <- HT (ones_b_B + ones_ab_B, diag(pi_B))
Xs <- cbind(delta_a, delta_ab, delta_ba, delta_b)
total <- c(Nhat_A - Nhat_abP, eta_0 * Nhat_abP, (1 - eta_0) * Nhat_abP, Nhat_B - Nhat_abP)
}
else {
Xs <- cbind(delta_a + delta_ab + delta_ba, delta_b + delta_ab + delta_ba)
total <- c(N_A, N_B)
}
}
else {
if (is.null(N_A) & is.null(N_B)) {
Xs <- cbind(delta_ab, delta_ba)
total <- c(eta_0 * N_ab, (1 - eta_0) * N_ab)
}else {
Xs <- cbind(delta_a, delta_ab, delta_ba, delta_b)
total <- c(N_A - N_ab, eta_0 * N_ab, (1 - eta_0) * N_ab, N_B - N_ab)
}
}
}
else {
if (is.null(N_ab)) {
if (is.null(xsAFrameA)){
if (is.null(xsBFrameB)){
xsT <- as.matrix(xsT)
Xs <- cbind(delta_a + delta_ab + delta_ba, delta_b + delta_ab + delta_ba, (delta_a + delta_ab + delta_b + delta_ba) * xsT)
total <- c(N_A, N_B, X)
}
else {
xsAFrameB <- as.matrix(xsAFrameB); xsBFrameB <- as.matrix(xsBFrameB)
XFrameB <- rbind(xsAFrameB, xsBFrameB)
if (is.null(xsT)){
Xs <- cbind(delta_a + delta_ab + delta_ba, delta_b + delta_ab + delta_ba, (delta_b + delta_ab + delta_ba) * XFrameB)
total <- c(N_A, N_B, XB)
}
else {
xsT <- as.matrix(xsT)
Xs <- cbind(delta_a + delta_ab + delta_ba, delta_b + delta_ab + delta_ba, (delta_b + delta_ab + delta_ba) * XFrameB, (delta_a + delta_ab + delta_b + delta_ba) * xsT)
total <- c(N_A, N_B, XB, X)
}
}
}
else {
xsAFrameA <- as.matrix(xsAFrameA); xsBFrameA <- as.matrix(xsBFrameA)
XFrameA <- rbind(xsAFrameA, xsBFrameA)
if (is.null(xsBFrameB)){
if (is.null(xsT)){
Xs <- cbind(delta_a + delta_ab + delta_ba, delta_b + delta_ab + delta_ba, (delta_a + delta_ab + delta_ba) * XFrameA)
total <- c(N_A, N_B, XA)
}
else{
xsT <- as.matrix(xsT)
Xs <- cbind(delta_a + delta_ab + delta_ba, delta_b + delta_ab + delta_ba, (delta_a + delta_ab + delta_ba) * XFrameA, (delta_a + delta_ab + delta_b + delta_ba) * xsT)
total <- c(N_A, N_B, XA, X)
}
}
else{
xsAFrameB <- as.matrix(xsAFrameB); xsBFrameB <- as.matrix(xsBFrameB)
XFrameB <- rbind(xsAFrameB, xsBFrameB)
if (is.null(xsT)){
Xs <- cbind(delta_a + delta_ab + delta_ba, delta_b + delta_ab + delta_ba, (delta_a + delta_ab + delta_ba) * XFrameA, (delta_b + delta_ab + delta_ba) * XFrameB)
total <- c(N_A, N_B, XA, XB)
}
else{
xsT <- as.matrix(xsT)
Xs <- Xs <- cbind(delta_a + delta_ab + delta_ba, delta_b + delta_ab + delta_ba, (delta_a + delta_ab + delta_ba) * XFrameA, (delta_b + delta_ab + delta_ba) * XFrameB, (delta_a + delta_ab + delta_b + delta_ba) * xsT)
total <- c(N_A, N_B, XA, XB, X)
}
}
}
}
else {
if (is.null(N_A) & is.null(N_B)) {
if (is.null(xsAFrameA)){
if (is.null(xsBFrameB)){
xsT <- as.matrix(xsT)
Xs <- cbind(delta_ab, delta_ba, xsT)
total <- c(eta_0 * N_ab, (1 - eta_0) * N_ab, X)
}
else {
xsAFrameB <- as.matrix(xsAFrameB); xsBFrameB <- as.matrix(xsBFrameB)
XFrameB <- rbind(xsAFrameB, xsBFrameB)
if (is.null(xsT)){
Xs <- cbind(delta_ab, delta_ba, (delta_b + delta_ab + delta_ba) * XFrameB)
total <- c(eta_0 * N_ab, (1 - eta_0) * N_ab, XB)
}
else {
xsT <- as.matrix(xsT)
Xs <- cbind(delta_ab, delta_ba, (delta_b + delta_ab + delta_ba) * XFrameB, (delta_a + delta_ab + delta_b + delta_ba) * xsT)
total <- c(eta_0 * N_ab, (1 - eta_0) * N_ab, XB, X)
}
}
}
else {
xsAFrameA <- as.matrix(xsAFrameA); xsBFrameA <- as.matrix(xsBFrameA)
XFrameA <- rbind(xsAFrameA, xsBFrameA)
if (is.null(xsBFrameB)){
if (is.null(xsT)){
Xs <- cbind(delta_ab, delta_ba, (delta_a + delta_ab + delta_ba) * XFrameA)
total <- c(eta_0 * N_ab, (1 - eta_0) * N_ab, XA)
}
else{
xsT <- as.matrix(xsT)
Xs <- cbind(delta_ab, delta_ba, (delta_a + delta_ab + delta_ba) * XFrameA, (delta_a + delta_ab + delta_b + delta_ba) * xsT)
total <- c(eta_0 * N_ab, (1 - eta_0) * N_ab, XA, X)
}
}
else{
xsAFrameB <- as.matrix(xsAFrameB); xsBFrameB <- as.matrix(xsBFrameB)
XFrameB <- rbind(xsAFrameB, xsBFrameB)
if (is.null(xsT)){
Xs <- cbind(delta_ab, delta_ba, (delta_a + delta_ab + delta_ba) * XFrameA, (delta_b + delta_ab + delta_ba) * XFrameB)
total <- c(eta_0 * N_ab, (1 - eta_0) * N_ab, XA, XB)
}
else{
xsT <- as.matrix(xsT)
Xs <- cbind(delta_ab, delta_ba, (delta_a + delta_ab + delta_ba) * XFrameA, (delta_b + delta_ab + delta_ba) * XFrameB, (delta_a + delta_ab + delta_b + delta_ba) * xsT)
total <- c(eta_0 * N_ab, (1 - eta_0) * N_ab, XA, XB, X)
}
}
}
}
else {
if (is.null(xsAFrameA)){
if (is.null(xsBFrameB)){
xsT <- as.matrix(xsT)
Xs <- cbind(delta_a, delta_ab, delta_b, delta_ba, xsT)
total <- c(N_A - N_ab, eta_0 * N_ab, N_B - N_ab, (1 - eta_0) * N_ab, X)
}
else {
xsAFrameB <- as.matrix(xsAFrameB); xsBFrameB <- as.matrix(xsBFrameB)
XFrameB <- rbind(xsAFrameB, xsBFrameB)
if (is.null(xsT)){
Xs <- cbind(delta_a, delta_ab, delta_b, delta_ba, (delta_b + delta_ab + delta_ba) * XFrameB)
total <- c(N_A - N_ab, eta_0 * N_ab, N_B - N_ab, (1 - eta_0) * N_ab, XB)
}
else {
xsT <- as.matrix(xsT)
Xs <- cbind(delta_a, delta_ab, delta_b, delta_ba, (delta_b + delta_ab + delta_ba) * XFrameB, (delta_a + delta_ab + delta_b + delta_ba) * xsT)
total <- c(N_A - N_ab, eta_0 * N_ab, N_B - N_ab, (1 - eta_0) * N_ab, XB, X)
}
}
}
else {
xsAFrameA <- as.matrix(xsAFrameA); xsBFrameA <- as.matrix(xsBFrameA)
XFrameA <- rbind(xsAFrameA, xsBFrameA)
if (is.null(xsBFrameB)){
if (is.null(xsT)){
Xs <- cbind(delta_a, delta_ab, delta_b, delta_ba, (delta_a + delta_ab + delta_ba) * XFrameA)
total <- c(N_A - N_ab, eta_0 * N_ab, N_B - N_ab, (1 - eta_0) * N_ab, XA)
}
else{
xsT <- as.matrix(xsT)
Xs <- cbind(delta_a, delta_ab, delta_b, delta_ba, (delta_a + delta_ab + delta_ba) * XFrameA, (delta_a + delta_ab + delta_b + delta_ba) * xsT)
total <- c(N_A - N_ab, eta_0 * N_ab, N_B - N_ab, (1 - eta_0) * N_ab, XA, X)
}
}
else{
xsAFrameB <- as.matrix(xsAFrameB); xsBFrameB <- as.matrix(xsBFrameB)
XFrameB <- rbind(xsAFrameB, xsBFrameB)
if (is.null(xsT)){
Xs <- cbind(delta_a, delta_ab, delta_b, delta_ba, (delta_a + delta_ab + delta_ba) * XFrameA, (delta_b + delta_ab + delta_ba) * XFrameB)
total <- c(N_A - N_ab, eta_0 * N_ab, N_B - N_ab, (1 - eta_0) * N_ab, XA, XB)
}
else{
xsT <- as.matrix(xsT)
Xs <- cbind(delta_a, delta_ab, delta_b, delta_ba, (delta_a + delta_ab + delta_ba) * XFrameA, (delta_b + delta_ab + delta_ba) * XFrameB, (delta_a + delta_ab + delta_b + delta_ba) * xsT)
total <- c(N_A - N_ab, eta_0 * N_ab, N_B - N_ab, (1 - eta_0) * N_ab, XA, XB, X)
}
}
}
}
}
}
results[,k] <- calib (Xs, d, total, method = met)
}
}
else {
if (is.null(dim(drop(pi_A))) & is.null(dim(drop(pi_B)))){
pik <- c(pi_A, pi_B)
dd <- 1/pik
Nhat_a_A <- HT (ones_a_A, pi_A)
Nhat_ab_A <- HT (ones_ab_A, pi_A)
Nhat_b_B <- HT (ones_b_B, pi_B)
Nhat_ab_B <- HT (ones_ab_B, pi_B)
Vhat_Nhat_ab_A <- varest(ones_ab_A, pik = pi_A)
Vhat_Nhat_ab_B <- varest(ones_ab_B, pik = pi_B)
eta_0 <- Vhat_Nhat_ab_B / (Vhat_Nhat_ab_A + Vhat_Nhat_ab_B)
for (k in 1:ncol(sample)) {
d <- dd*delta_a + dd*eta_0*delta_ab + dd*(1-eta_0)*delta_ba + dd*delta_b
if (is.null(xsAFrameA) & is.null(xsBFrameB) & is.null(xsT)) {
if (is.null(N_ab)) {
if (is.null(N_A) & is.null(N_B)) {
Nhat_abP <- eta_0 * Nhat_ab_A + (1 - eta_0) * Nhat_ab_B
Nhat_A <- HT (ones_a_A + ones_ab_A, pi_A)
Nhat_B <- HT (ones_b_B + ones_ab_B, pi_B)
Xs <- cbind(delta_a, delta_ab, delta_ba, delta_b)
total <- c(Nhat_A - Nhat_abP, eta_0 * Nhat_abP, (1 - eta_0) * Nhat_abP, Nhat_B - Nhat_abP)
}
else {
Xs <- cbind(delta_a + delta_ab + delta_ba, delta_b + delta_ab + delta_ba)
total <- c(N_A, N_B)
}
}
else {
if (is.null(N_A) & is.null(N_B)) {
Xs <- cbind(delta_ab, delta_ba)
total <- c(eta_0 * N_ab, (1 - eta_0) * N_ab)
}
else {
Xs <- cbind(delta_a, delta_ab, delta_ba, delta_b)
total <- c(N_A - N_ab, eta_0 * N_ab, (1 - eta_0) * N_ab, N_B - N_ab)
}
}
}
else {
if (is.null(N_ab)) {
if (is.null(xsAFrameA)){
if (is.null(xsBFrameB)){
xsT <- as.matrix(xsT)
Xs <- cbind(delta_a + delta_ab + delta_ba, delta_b + delta_ab + delta_ba, (delta_a + delta_ab + delta_b + delta_ba) * xsT)
total <- c(N_A, N_B, X)
}
else {
xsAFrameB <- as.matrix(xsAFrameB); xsBFrameB <- as.matrix(xsBFrameB)
XFrameB <- rbind(xsAFrameB, xsBFrameB)
if (is.null(xsT)){
Xs <- cbind(delta_a + delta_ab + delta_ba, delta_b + delta_ab + delta_ba, (delta_b + delta_ab + delta_ba) * XFrameB)
total <- c(N_A, N_B, XB)
}
else {
xsT <- as.matrix(xsT)
Xs <- cbind(delta_a + delta_ab + delta_ba, delta_b + delta_ab + delta_ba, (delta_b + delta_ab + delta_ba) * XFrameB, (delta_a + delta_ab + delta_b + delta_ba) * xsT)
total <- c(N_A, N_B, XB, X)
}
}
}
else {
xsAFrameA <- as.matrix(xsAFrameA); xsBFrameA <- as.matrix(xsBFrameA)
XFrameA <- rbind(xsAFrameA, xsBFrameA)
if (is.null(xsBFrameB)){
if (is.null(xsT)){
Xs <- cbind(delta_a + delta_ab + delta_ba, delta_b + delta_ab + delta_ba, (delta_a + delta_ab + delta_ba) * XFrameA)
total <- c(N_A, N_B, XA)
}
else{
xsT <- as.matrix(xsT)
Xs <- cbind(delta_a + delta_ab + delta_ba, delta_b + delta_ab + delta_ba, (delta_a + delta_ab + delta_ba) * XFrameA, (delta_a + delta_ab + delta_b + delta_ba) * xsT)
total <- c(N_A, N_B, XA, X)
}
}
else{
xsAFrameB <- as.matrix(xsAFrameB); xsBFrameB <- as.matrix(xsBFrameB)
XFrameB <- rbind(xsAFrameB, xsBFrameB)
if (is.null(xsT)){
Xs <- cbind(delta_a + delta_ab + delta_ba, delta_b + delta_ab + delta_ba, (delta_a + delta_ab + delta_ba) * XFrameA, (delta_b + delta_ab + delta_ba) * XFrameB)
total <- c(N_A, N_B, XA, XB)
}
else{
xsT <- as.matrix(xsT)
Xs <- Xs <- cbind(delta_a + delta_ab + delta_ba, delta_b + delta_ab + delta_ba, (delta_a + delta_ab + delta_ba) * XFrameA, (delta_b + delta_ab + delta_ba) * XFrameB, (delta_a + delta_ab + delta_b + delta_ba) * xsT)
total <- c(N_A, N_B, XA, XB, X)
}
}
}
}
else {
if (is.null(N_A) & is.null(N_B)) {
if (is.null(xsAFrameA)){
if (is.null(xsBFrameB)){
xsT <- as.matrix(xsT)
Xs <- cbind(delta_ab, delta_ba, xsT)
total <- c(eta_0 * N_ab, (1 - eta_0) * N_ab, X)
}
else {
xsAFrameB <- as.matrix(xsAFrameB); xsBFrameB <- as.matrix(xsBFrameB)
XFrameB <- rbind(xsAFrameB, xsBFrameB)
if (is.null(xsT)){
Xs <- cbind(delta_ab, delta_ba, (delta_b + delta_ab + delta_ba) * XFrameB)
total <- c(eta_0 * N_ab, (1 - eta_0) * N_ab, XB)
}
else {
xsT <- as.matrix(xsT)
Xs <- cbind(delta_ab, delta_ba, (delta_b + delta_ab + delta_ba) * XFrameB, (delta_a + delta_ab + delta_b + delta_ba) * xsT)
total <- c(eta_0 * N_ab, (1 - eta_0) * N_ab, XB, X)
}
}
}
else {
xsAFrameA <- as.matrix(xsAFrameA); xsBFrameA <- as.matrix(xsBFrameA)
XFrameA <- rbind(xsAFrameA, xsBFrameA)
if (is.null(xsBFrameB)){
if (is.null(xsT)){
Xs <- cbind(delta_ab, delta_ba, (delta_a + delta_ab + delta_ba) * XFrameA)
total <- c(eta_0 * N_ab, (1 - eta_0) * N_ab, XA)
}
else{
xsT <- as.matrix(xsT)
Xs <- cbind(delta_ab, delta_ba, (delta_a + delta_ab + delta_ba) * XFrameA, (delta_a + delta_ab + delta_b + delta_ba) * xsT)
total <- c(eta_0 * N_ab, (1 - eta_0) * N_ab, XA, X)
}
}
else{
xsAFrameB <- as.matrix(xsAFrameB); xsBFrameB <- as.matrix(xsBFrameB)
XFrameB <- rbind(xsAFrameB, xsBFrameB)
if (is.null(xsT)){
Xs <- cbind(delta_ab, delta_ba, (delta_a + delta_ab + delta_ba) * XFrameA, (delta_b + delta_ab + delta_ba) * XFrameB)
total <- c(eta_0 * N_ab, (1 - eta_0) * N_ab, XA, XB)
}
else{
xsT <- as.matrix(xsT)
Xs <- cbind(delta_ab, delta_ba, (delta_a + delta_ab + delta_ba) * XFrameA, (delta_b + delta_ab + delta_ba) * XFrameB, (delta_a + delta_ab + delta_b + delta_ba) * xsT)
total <- c(eta_0 * N_ab, (1 - eta_0) * N_ab, XA, XB, X)
}
}
}
}
else {
if (is.null(xsAFrameA)){
if (is.null(xsBFrameB)){
xsT <- as.matrix(xsT)
Xs <- cbind(delta_a, delta_ab, delta_b, delta_ba, xsT)
total <- c(N_A - N_ab, eta_0 * N_ab, N_B - N_ab, (1 - eta_0) * N_ab, X)
}
else {
xsAFrameB <- as.matrix(xsAFrameB); xsBFrameB <- as.matrix(xsBFrameB)
XFrameB <- rbind(xsAFrameB, xsBFrameB)
if (is.null(xsT)){
Xs <- cbind(delta_a, delta_ab, delta_b, delta_ba, (delta_b + delta_ab + delta_ba) * XFrameB)
total <- c(N_A - N_ab, eta_0 * N_ab, N_B - N_ab, (1 - eta_0) * N_ab, XB)
}
else {
xsT <- as.matrix(xsT)
Xs <- cbind(delta_a, delta_ab, delta_b, delta_ba, (delta_b + delta_ab + delta_ba) * XFrameB, (delta_a + delta_ab + delta_b + delta_ba) * xsT)
total <- c(N_A - N_ab, eta_0 * N_ab, N_B - N_ab, (1 - eta_0) * N_ab, XB, X)
}
}
}
else {
xsAFrameA <- as.matrix(xsAFrameA); xsBFrameA <- as.matrix(xsBFrameA)
XFrameA <- rbind(xsAFrameA, xsBFrameA)
if (is.null(xsBFrameB)){
if (is.null(xsT)){
Xs <- cbind(delta_a, delta_ab, delta_b, delta_ba, (delta_a + delta_ab + delta_ba) * XFrameA)
total <- c(N_A - N_ab, eta_0 * N_ab, N_B - N_ab, (1 - eta_0) * N_ab, XA)
}
else{
xsT <- as.matrix(xsT)
Xs <- cbind(delta_a, delta_ab, delta_b, delta_ba, (delta_a + delta_ab + delta_ba) * XFrameA, (delta_a + delta_ab + delta_b + delta_ba) * xsT)
total <- c(N_A - N_ab, eta_0 * N_ab, N_B - N_ab, (1 - eta_0) * N_ab, XA, X)
}
}
else{
xsAFrameB <- as.matrix(xsAFrameB); xsBFrameB <- as.matrix(xsBFrameB)
XFrameB <- rbind(xsAFrameB, xsBFrameB)
if (is.null(xsT)){
Xs <- cbind(delta_a, delta_ab, delta_b, delta_ba, (delta_a + delta_ab + delta_ba) * XFrameA, (delta_b + delta_ab + delta_ba) * XFrameB)
total <- c(N_A - N_ab, eta_0 * N_ab, N_B - N_ab, (1 - eta_0) * N_ab, XA, XB)
}
else{
xsT <- as.matrix(xsT)
Xs <- cbind(delta_a, delta_ab, delta_b, delta_ba, (delta_a + delta_ab + delta_ba) * XFrameA, (delta_b + delta_ab + delta_ba) * XFrameB, (delta_a + delta_ab + delta_b + delta_ba) * xsT)
total <- c(N_A - N_ab, eta_0 * N_ab, N_B - N_ab, (1 - eta_0) * N_ab, XA, XB, X)
}
}
}
}
}
}
results[,k] <- calib (Xs, d, total, method = met)
}
}
else
stop("Invalid option: Probability vector in one frame and probability matrix in the other frame. Type of both structures must match.")
}
return (results)
}
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