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Add check_convergence method for parsnip _glm model #605

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merged 4 commits into from
Sep 10, 2023
Merged

Add check_convergence method for parsnip _glm model #605

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db9190e
Add method for parsnip _glm model
egouldo Sep 4, 2023
96f85bc
Merge branch 'main' into patch-1
strengejacke Sep 10, 2023
694c46f
Update NAMESPACE
strengejacke Sep 10, 2023
75e65ad
lintr
strengejacke Sep 10, 2023
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1 change: 1 addition & 0 deletions NAMESPACE
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Original file line number Diff line number Diff line change
Expand Up @@ -45,6 +45,7 @@ S3method(check_collinearity,probitmfx)
S3method(check_collinearity,zerocount)
S3method(check_collinearity,zeroinfl)
S3method(check_concurvity,gam)
S3method(check_convergence,"_glm")
S3method(check_convergence,default)
S3method(check_convergence,glmmTMB)
S3method(check_convergence,merMod)
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6 changes: 6 additions & 0 deletions R/check_convergence.R
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Expand Up @@ -32,7 +32,7 @@
#' how to resolve convergence issues. Another clue might be large parameter
#' values, e.g. estimates (on the scale of the linear predictor) larger than
#' 10 in (non-identity link) generalized linear model *might* indicate
#' [complete separation](https://stats.oarc.ucla.edu/other/mult-pkg/faq/general/faqwhat-is-complete-or-quasi-complete-separation-in-logisticprobit-regression-and-how-do-we-deal-with-them/).

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file=R/check_convergence.R,line=35,col=121,[line_length_linter] Lines should not be more than 120 characters. This line is 189 characters.
#' Complete separation can be addressed by regularization, e.g. penalized
#' regression or Bayesian regression with appropriate priors on the fixed effects.
#'
Expand Down Expand Up @@ -107,3 +107,9 @@
# https://github.com/glmmTMB/glmmTMB/issues/275
isTRUE(x$sdr$pdHess)
}


#' @export
check_convergence._glm <- function(x, ...) {
isTRUE(x$fit$converged)
}
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