1d:T5df,# Method for computing confidence intervals for one or more regression parameters in a `"mdyplFit"` object ```r ## S3 method for class 'mdyplFit' confint(object, parm, level = 0.95, hd_correction = FALSE, ...) ``` ## Arguments - `object`: a fitted model object. - `parm`: a specification of which parameters are to be given confidence intervals, either a vector of numbers or a vector of names. If missing, all parameters are considered. - `level`: the confidence level required. - `hd_correction`: if `FALSE` (default), then the corresponding quantities are computed according to standard asymptotics. If `TRUE` then the high-dimensionality corrections in Sterzinger & Kosmidis (2024) are employed to updates estimates, estimated standard errors, z-statistics, etc. See Details. - `...`: additional argument(s) for methods. ## Examples ```r set.seed(123) n <- 2000 p <- 800 set.seed(123) betas <- c(rnorm(p / 4, mean = 7, sd = 1), rep(0, 3 * p / 4)) X <- matrix(rnorm(n * p, 0, 1/sqrt(n)), nrow = n, ncol = p) probs <- plogis(drop(X %*% betas)) y <- rbinom(n, 1, probs) fit_mdypl <- glm(y ~ -1 + X, family = binomial(), method = "mdyplFit") wald_ci <- confint(fit_mdypl) adj_wald_ci <- confint(fit_mdypl, hd_correction = TRUE) ag_coverage <- function(cis, beta) mean((cis[, 1] < beta) & (cis[, 2] > beta)) ag_coverage(wald_ci, betas) ag_coverage(adj_wald_ci, betas) ``` ## See Also `mdyplFit()`, `summary.mdyplFit()` ## Author(s) Ioannis Kosmidis `[aut, cre]` ioannis.kosmidis@warwick.ac.uk1e:T49a,M7.49933 0.25C3.49635 0.25 0.25 3.49593 0.25 7.50024C0.25 10.703 2.32715 13.4206 5.2081 14.3797C5.57084 14.446 5.70302 14.2222 5.70302 14.0299C5.70302 13.8576 5.69679 13.4019 5.69323 12.797C3.67661 13.235 3.25112 11.825 3.25112 11.825C2.92132 10.9874 2.44599 10.7644 2.44599 10.7644C1.78773 10.3149 2.49584 10.3238 2.49584 10.3238C3.22353 10.375 3.60629 11.0711 3.60629 11.0711C4.25298 12.1788 5.30335 11.8588 5.71638 11.6732C5.78225 11.205 5.96962 10.8854 6.17658 10.7043C4.56675 10.5209 2.87415 9.89918 2.87415 7.12104C2.87415

confint.mdyplFit function