/
gmm-tidiers.R
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gmm-tidiers.R
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#' @templateVar class gmm
#' @template title_desc_tidy
#'
#' @param x A `gmm` object returned from [gmm::gmm()].
#' @template param_confint
#' @template param_exponentiate
#' @template param_unused_dots
#'
#' @evalRd return_tidy(regression = TRUE)
#'
#' @examplesIf rlang::is_installed(c("gmm", "ggplot2"))
#'
#' # load libraries for models and data
#' library(gmm)
#'
#' # examples come from the "gmm" package
#' # CAPM test with GMM
#' data(Finance)
#' r <- Finance[1:300, 1:10]
#' rm <- Finance[1:300, "rm"]
#' rf <- Finance[1:300, "rf"]
#'
#' z <- as.matrix(r - rf)
#' t <- nrow(z)
#' zm <- rm - rf
#' h <- matrix(zm, t, 1)
#' res <- gmm(z ~ zm, x = h)
#'
#' # tidy result
#' tidy(res)
#' tidy(res, conf.int = TRUE)
#' tidy(res, conf.int = TRUE, conf.level = .99)
#'
#' # coefficient plot
#' library(ggplot2)
#' library(dplyr)
#'
#' tidy(res, conf.int = TRUE) %>%
#' mutate(variable = reorder(term, estimate)) %>%
#' ggplot(aes(estimate, variable)) +
#' geom_point() +
#' geom_errorbarh(aes(xmin = conf.low, xmax = conf.high)) +
#' geom_vline(xintercept = 0, color = "red", lty = 2)
#'
#' # from a function instead of a matrix
#' g <- function(theta, x) {
#' e <- x[, 2:11] - theta[1] - (x[, 1] - theta[1]) %*% matrix(theta[2:11], 1, 10)
#' gmat <- cbind(e, e * c(x[, 1]))
#' return(gmat)
#' }
#'
#' x <- as.matrix(cbind(rm, r))
#' res_black <- gmm(g, x = x, t0 = rep(0, 11))
#'
#' tidy(res_black)
#' tidy(res_black, conf.int = TRUE)
#'
#' # APT test with Fama-French factors and GMM
#'
#' f1 <- zm
#' f2 <- Finance[1:300, "hml"] - rf
#' f3 <- Finance[1:300, "smb"] - rf
#' h <- cbind(f1, f2, f3)
#' res2 <- gmm(z ~ f1 + f2 + f3, x = h)
#'
#' td2 <- tidy(res2, conf.int = TRUE)
#' td2
#'
#' # coefficient plot
#' td2 %>%
#' mutate(variable = reorder(term, estimate)) %>%
#' ggplot(aes(estimate, variable)) +
#' geom_point() +
#' geom_errorbarh(aes(xmin = conf.low, xmax = conf.high)) +
#' geom_vline(xintercept = 0, color = "red", lty = 2)
#'
#' @export
#' @aliases gmm_tidiers
#' @family gmm tidiers
#' @seealso [tidy()], [gmm::gmm()]
tidy.gmm <- function(x, conf.int = FALSE, conf.level = .95,
exponentiate = FALSE, ...) {
coef <- summary(x)$coefficients
ret <- as_tibble(coef, rownames = "term")
colnames(ret) <- c("term", "estimate", "std.error", "statistic", "p.value")
if (conf.int) {
# non-standard confint return object, so can't use
# broom_confint_terms() like we'd hope
ci <- confint(x, level = conf.level)$test
ci <- as_tibble(ci, rownames = "term")
colnames(ci) <- c("term", "conf.low", "conf.high")
ret <- dplyr::left_join(ret, ci, by = "term")
}
if (exponentiate) {
ret <- exponentiate(ret)
}
ret
}
#' @templateVar class gmm
#' @template title_desc_glance
#'
#' @inherit tidy.gmm params examples
#'
#' @evalRd return_glance("df",
#' "statistic",
#' "p.value",
#' "df.residual",
#' "nobs")
#'
#' @export
#' @family gmm tidiers
#' @seealso [glance()], [gmm::gmm()]
glance.gmm <- function(x, ...) {
s <- summary(x)
# TODO: why do we suppress warnings here?
st <- suppressWarnings(as.numeric(s$stest$test))
as_glance_tibble(
df = x$df,
statistic = st[1],
p.value = st[2],
df.residual = stats::df.residual(x),
nobs = stats::nobs(x),
na_types = "irrii"
)
}