Fit and plot maturity ogives

Fit and plot maturity ogives

fit_mat_ogive(dat, type = c("age", "length"), sample_id_re = FALSE,
  months = seq(1, 12), ageing_method_codes = NULL,
  usability_codes = c(0, 1, 2, 6))

plot_mat_ogive(object, xlab = if (object$type[[1]] == "age")
  "Age (years)" else "Length (cm)", title = if (object$type[[1]] ==
  "age") "Age at maturity" else "Length at maturity", rug = TRUE,
  rug_n = 1500, x_max = 1.75, prediction_type = c("all", "male",
  "female", "none"))

Arguments

dat	Data from get_survey_samples().
type	Should this be an age or length fit?
sample_id_re	If TRUE then the model will include random intercepts for sample ID.
months	A numeric vector indicating which months to include when fitting the maturity ogive. Defaults to all months.
ageing_method_codes	A numeric vector of ageing method codes to filter on. Defaults to NULL, which brings in all valid ageing codes. See get_age_methods().
usability_codes	An optional vector of usability codes. All usability codes not in this vector will be omitted. Set to NULL to include all samples.
object	Output from fit_mat_ogive().
xlab	X axis label.
title	Title for the plot.
rug	Logical indicating whether rug lines should be added.
rug_n	The number of rug lines to sample from the total number of fish.
x_max	Used in determining the right axis limit.
prediction_type	The prediction lines to show. Useful if you only want to show model fits when you have sufficient data.

Examples

# d <- get_survey_samples("pacific ocean perch", ssid = 1)
d <- pop_samples

m <- fit_mat_ogive(d, type = "age", sample_id_re = FALSE)
#> Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
plot_mat_ogive(m)

m <- fit_mat_ogive(d, type = "length", sample_id_re = FALSE)
plot_mat_ogive(m)

# NOT RUN {
## with random intercepts for sample ID:
m <- fit_mat_ogive(d, type = "length", sample_id_re = TRUE)
plot_mat_ogive(m)
# }