#' Take a glance at a model
#'
#' Construct a single row of model summary statistics.
#'
#' @param x An object of class `timedist`.
#'
#' @return `glance()` returns a one row `data.frame` with the columns
#' \item{sigma}{the square root of the estimated residual variance}
#' \item{isConv}{whether the fit successfully converged}
#' \item{finTol}{the achieved convergence tolerance}
#' \item{logLik}{the data's log-likelihood under the model}
#' \item{AIC}{the Akaike Information Criterion}
#' \item{BIC}{the Bayesian Information Criterion}
#' \item{deviance}{deviance}
#' \item{df.residual}{residual degrees of freedom}
#' \item{RSS}{corrected residual sum of squares}
#' \item{nobs}{the number of observations from the model fit}
#'
#' @examples
#' tdTilia <- tdData(tilia, x = "Day", y = "Trees")
#' model <- timedist(data = tdTilia, x = "Day", y = "propMax", r = 0.1, c = 0.5, t = 120)
#' glance(model)
#'
#' @importFrom stats logLik AIC BIC deviance df.residual nobs
#'
#' @export
glance <- function(x) {
s <- summary(x)
data.frame(
sigma = s$sigma,
isConv = s$convInfo$isConv,
finTol = s$convInfo$finTol,
logLik = as.numeric(stats::logLik(x)),
AIC = stats::AIC(x),
BIC = stats::BIC(x),
deviance = stats::deviance(x),
df.residual = stats::df.residual(x),
RSS = tdRSS(x),
nobs = stats::nobs(x)
)
}
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