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replace estimate_extraction.R with faster version #8

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replace estimate_extraction.R with faster version #8

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29 changes: 28 additions & 1 deletion R/estimate_extraction.R
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Original file line number Diff line number Diff line change
Expand Up @@ -30,7 +30,7 @@
#'
#' @return The value of the estimate as a single number.
#'
#' @importFrom stats lm
#' @importFrom stats lm pf
#' @name estimate_extraction

#' @rdname estimate_extraction
Expand Down Expand Up @@ -77,6 +77,16 @@ f <- function(object, data = NULL, all = FALSE, predictor = character(), type =
check_extract_args(all, predictor, type)
fit <- convert_lm(object, {{ data }})
suppressMessages(check_empty_model(fit))

# Fast path: overall F statistic without building full supernova table
# This provides ~5x speedup for bootstrapping use cases
if (!all && is_empty(predictor)) {
fstat <- summary(fit)$fstatistic
if (is.null(fstat)) return(NA_real_)
return(unname(fstat[1]))
}

# Full path: need supernova table for predictor-specific or all statistics
stats <- extract_stat(fit, type, "F", predictor)
if (all || !is_empty(predictor)) stats else stats[[1]]
}
Expand All @@ -88,6 +98,13 @@ pre <- function(object, data = NULL, all = FALSE, predictor = character(), type
check_extract_args(all, predictor, type)
fit <- convert_lm(object, {{ data }})
check_empty_model(fit)

# Fast path: overall PRE (R-squared) without building full supernova table
if (!all && is_empty(predictor)) {
return(summary(fit)$r.squared)
}

# Full path: need supernova table for predictor-specific or all statistics
stats <- extract_stat(fit, type, "PRE", predictor)
if (all || !is_empty(predictor)) stats else stats[[1]]
}
Expand All @@ -99,6 +116,16 @@ p <- function(object, data = NULL, all = FALSE, predictor = character(), type =
check_extract_args(all, predictor, type)
fit <- convert_lm(object, {{ data }})
check_empty_model(fit)

# Fast path: overall p-value computed directly from F statistic
if (!all && is_empty(predictor)) {
fstat <- summary(fit)$fstatistic
if (is.null(fstat)) return(NA_real_)
# fstat contains: F value, numerator df, denominator df
return(unname(pf(fstat[1], fstat[2], fstat[3], lower.tail = FALSE)))
}

# Full path: need supernova table for predictor-specific or all statistics
stats <- extract_stat(fit, type, "p", predictor)
if (all || !is_empty(predictor)) stats else stats[[1]]
}
Expand Down
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