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#' @title Compute Partial Derivatives of Expected Values for a Positive Poisson Model
#'
#' @description
#' This internal function calculates the partial derivatives of expected values
#' for a positive Poisson regression model with respect to covariates.
#' It also computes marginal effects for specified dummy variables.
#'
#' @param b Numeric vector of coefficients for the Poisson model.
#' @param X Matrix of predictors for the Poisson model, where rows correspond
#' to observations and columns to covariates.
#' @param dummies Character vector of column names from `X` that are treated
#' as dummy variables for which marginal effects are computed.
#'
#' @return
#' A matrix of partial derivatives (or marginal effects) with rows corresponding to observations
#' and columns to covariates. Marginal effects for dummy variables are calculated by contrasting
#' expected values when the dummy is set to 0 versus 1.
#'
#' @details
#' This function:
#' - Computes partial derivatives of expected values with respect to covariates in `X`.
#' - Handles marginal effects for dummy variables by modifying their values in the design matrix
#' and computing the difference in expected values.
#'
#' It is designed for internal use and assumes correct input structure. Improper inputs may result
#' in errors or unexpected behavior.
#'
#' @seealso
#' \code{\link{E_pois_noinfl}} for computing expected values in the positive Poisson model.
#'
#' @keywords internal
dEdq_pois_noinfl <- function(b, X, dummies, formula) {
l <- exp(X %*% b)
vars <- attr(terms(formula), "term.labels")
num_unique <- length(unique(vars))
dldq <- matrix(, nrow(X), num_unique)
colnames(dldq) <- vars
dldq[, colnames(X)[-1]] <- l %*% b[-1]
dldq[, -which(colnames(dldq) %in% colnames(X)[-1])] <- 0L
# Do the math
dEdq <- dldq * exp(l) * (exp(l) - l - 1) / ((exp(l) - 1) ^ 2)
# Calculate the "marginal" effect for dummies properly
if(length(dummies) == 0) {return(dEdq)}
else {
for(i in 1:length(dummies)) {
Xd1 <- Xd0 <- X
Xd1[ , dummies[i] == colnames(X)] <- 1
Xd0[ , dummies[i] == colnames(X)] <- 0
dEdq[, dummies[i]] <- E_pois_noinfl(b, X=Xd1) - E_pois_noinfl(b, X=Xd0)
}
return(dEdq)
}
}
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