Parametric-bootstrap confidence envelope for a heat-injury trajectory

heat_injury_envelope() is the uncertainty counterpart of predict_heat_injury(): it redraws the fitted curve parameters by parametric bootstrap (the same machinery confint() uses), re-integrates the survival trajectory under the temperature trace for each draw with the documented dose-accumulation map, and returns a pointwise confidence band around the point-estimate survival curve. The band is prior-free – it carries no prior and makes no probability statement about the parameters; it is the likelihood-path analogue of the bayesTLS posterior survival band, not a credible band.

Usage

heat_injury_envelope(
  object,
  trace,
  group = NULL,
  target_surv = NULL,
  t_c = NULL,
  repair = NULL,
  irreversible = TRUE,
  nboot = 1000L,
  conf.level = 0.95,
  seed = NULL
)

Arguments

object: A profile_tls fit from fit_tls(), or a freq_tls workflow from fit_4pl().
trace: A data frame with numeric columns time (strictly increasing, at least two rows) and temp (degrees C).
group: Optional single group level (grouped fits only; required when the fit is grouped).
target_surv: Optional absolute survival threshold defining one lethal dose: a single probability strictly between the fitted lower and upper asymptotes. NULL (default) uses the project-default relative threshold (the curve midpoint (low + up) / 2), matching derive_ctmax() and derive_lt(). For a bootstrap envelope the target must also be attainable in every converged bootstrap refit; otherwise the function aborts rather than clipping an invalid refit's threshold.
t_c: Optional damage-cutoff temperature (degrees C): at or below it the damage rate is zero. NULL (default) applies no cutoff.
repair: Optional named list of Sharpe-Schoolfield repair parameters (see Details); NULL (default) means no repair.
irreversible: Logical; if TRUE (default) survival is monotone non-increasing (mortality does not reverse even if dose is repaired).
nboot: Number of bootstrap replicates (default 1000).
conf.level: Width of the pointwise confidence band (default 0.95).
seed: Optional integer seed; when supplied the bootstrap is reproducible without disturbing the caller's random stream.

Value

A tibble with time, temp, survival (the point-estimate trajectory from predict_heat_injury()), and conf.low / conf.high (the pointwise parametric-bootstrap confidence band).

Examples

d <- simulate_tls(family = "binomial", CTmax = 36, z = 4, seed = 1)
fit <- fit_tls(d, y = survived, n = total, time = duration, temp = temp,
               family = "binomial", tref = 1)
trace <- data.frame(time = seq(0, 2, by = 0.1),
                    temp = 34 + 6 * sin(seq(0, 2, by = 0.1)))
heat_injury_envelope(fit, trace, nboot = 50, seed = 1)
#> # A tibble: 21 × 5
#>     time  temp survival conf.low conf.high
#>    <dbl> <dbl>    <dbl>    <dbl>     <dbl>
#>  1   0    34      0.977    0.963     0.994
#>  2   0.1  34.6    0.977    0.963     0.992
#>  3   0.2  35.2    0.973    0.960     0.985
#>  4   0.3  35.8    0.962    0.946     0.973
#>  5   0.4  36.3    0.935    0.913     0.954
#>  6   0.5  36.9    0.878    0.837     0.911
#>  7   0.6  37.4    0.776    0.718     0.832
#>  8   0.7  37.9    0.629    0.556     0.697
#>  9   0.8  38.3    0.462    0.391     0.529
#> 10   0.9  38.7    0.314    0.251     0.375
#> # ℹ 11 more rows