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Monte Carlo Simulation of Survivorship

Source: R/simulate_survivorship.R
simulate_survivorship.Rd

Simulates cohort survivorship trajectories using age-specific mortality schedules. Computes cumulative survival, mean age at death, and probabilities of reaching maturity and maximum age.

Usage

simulate_survivorship(
  mc_object,
  n = 50000,
  n_iter = 5000,
  mode = c("random", "per_set"),
  seed = 1234,
  palette = c("synthwave", "viridis", "okabe", "plasma", "inferno"),
  bar_fill = NULL,
  bar_color = NULL,
  bar_alpha = 0.7,
  error_color = "black",
  error_width = 0.4,
  vline_color = NULL,
  vline_width = 1,
  vline_type = "solid",
  rect_fill = NULL,
  rect_alpha = 0.4,
  x_breaks = function(tmax) seq(0, ceiling(tmax), by = 5),
  title = NULL,
  subtitle = "Aggregated across simulations",
  base_size = 11,
  font_family = "serif",
  print_plot = TRUE,
  show_progress = TRUE
)

Arguments

mc_object

Output from get_stochastic_mortality(), containing $Schedules and $Parameters.

n

Starting cohort size. Default 50000.

n_iter

Number of simulation iterations. Default 5000.

mode

Character. Either:

  • "random" - Each iteration uses a randomly sampled parameter set

  • "per_set" - Run n_iter simulations for each parameter set

seed

Random seed. Default 1234.

palette

Color palette: "synthwave", "viridis", "okabe".

bar_fill, bar_color

Colors for survivorship bars.

bar_alpha

Transparency for bars. Default 0.7.

error_color

Color for error bars. Default "black".

error_width

Width of error bars. Default 0.4.

vline_color, vline_width, vline_type

Mean age-at-death line aesthetics.

rect_fill, rect_alpha

Uncertainty band for mean age-at-death.

x_breaks

Function returning x-axis breaks given max tmax.

title, subtitle

Plot title and subtitle.

base_size

Base font size. Default 11.

font_family

Font family. Default "serif".

print_plot

Print plot? Default TRUE.

show_progress

Show progress messages? Default TRUE.

Value

A list with:

Aggregate

List with overall survival curve, age-at-death, and survival probabilities to tmat/tmax

Per_Set

List with per-parameter-set summaries

Raw

data.table of all trajectory data

Plot

ggplot2 object

Details

For each iteration, the function:

  1. Integrates the mortality schedule to get cumulative survival: \(S(t) = \exp(-\int_0^t M(a) da)\)

  2. Simulates discrete cohort transitions using binomial survival

  3. Tracks deaths to compute age-at-death distribution

Examples

if (FALSE) { # \dontrun{
mort <- get_stochastic_mortality(method = "CW", ...)
surv <- simulate_survivorship(mort, n = 1e5, n_iter = 2000)
surv$Plot
} # }