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fit_truncated_dist() is deprecated as of version 0.9.0. Use fit_truncated_severity() instead.

Usage

fit_truncated_dist(
  losses = NULL,
  distribution = c("gamma", "lognormal"),
  lower_truncation = NULL,
  upper_truncation = NULL,
  start_values = NULL,
  print_initial = TRUE,
  n_variants = 1,
  n_shape_grid = 8,
  n_scale_grid = 8,
  show_progress = FALSE,
  show_summary = TRUE,
  y = NULL,
  dist = NULL,
  left = NULL,
  right = NULL,
  start = NULL,
  trace = NULL,
  report = NULL
)

Arguments

losses

Numeric vector with observed claim severities.

distribution

Severity distribution to fit: "gamma" or "lognormal".

lower_truncation

Numeric lower truncation point. Claims at or below this value are assumed not to be present in losses. Defaults to 0.

upper_truncation

Numeric upper truncation point. Claims at or above this value are assumed not to be present in losses. Defaults to Inf.

start_values

Optional named list of starting values. If NULL, a multi-start strategy is used. For a gamma distribution use shape and scale; for a lognormal distribution use meanlog and sdlog.

print_initial

Deprecated logical retained for backward compatibility.

n_variants

Controls how many local variations around base starts are used.

n_shape_grid

Number of grid points for gamma shape.

n_scale_grid

Number of grid points for gamma scale.

show_progress

Logical. If TRUE, prints periodic progress during the fitting loop.

show_summary

Logical. If TRUE, prints a short summary at the end.

y, dist, left, right, start, trace, report

Deprecated argument names kept for backward compatibility.