Plot maturity ogive — plot_maturity • ggFishPlots

Plots an estimate of length or age at 50% mature for a dataset

Usage

plot_maturity(
  dt,
  length = "length",
  maturity = "maturity",
  sex = "sex",
  split.by.sex = FALSE,
  female.sex = "F",
  male.sex = "M",
  length.unit = "cm",
  length.bin.width = 2,
  bootstrap.n = NA,
  force.zero.group.length = NA,
  force.zero.group.strength = NA,
  force.zero.group.n = NA,
  force.zero.group.cv = 0,
  xlab = "Total length",
  base_size = 8,
  legend.position = "bottom",
  ...
)

Arguments

dt: A data.frame, tibble or data.table
length: Character argument giving the name of the length (or age) column in dt
maturity: Character argument giving the name of the maturity column in dt. Should be either logical (TRUE == mature, FALSE == immature) or integer (1 == mature, 0 == immature).
sex: Character argument giving the name of the sex column in dt. Ignored if split.by.sex == FALSE.
split.by.sex: Logical indicating whether the result should be split by sex.
female.sex, male.sex: A character or integer denoting female and male sex in the sex column of dt, respectively.
length.unit: A character argument giving the unit of length. Will be used in the labels of the figure.
length.bin.width: Numeric specifying the increment (delta length) by which length data should be binned to calculate maturity proportions. Use NULL to remove from the plot.
bootstrap.n: Integer defining the number of bootstrap replicates to be used to calculate 95% confidence intervals for the mean 50% mature estimate. If NA (default), the confidence intervals are calculated from the glm object without boostrapping. See Details.
force.zero.group.length: Numeric indicating the length to which 0-group (all immatures) should be forced. Use NA ignore the forcing.
force.zero.group.strength: Numeric indicating how many percent of total fish should be added to the specified force.zero.group.length. Cannot be used simultaneously with force.zero.group.n
force.zero.group.n: Numeric indicating how many observations should be added to the specified force.zero.group.length. If split.by.sex = TRUE, use a named vector of length two with names referring to female.sex and male.sex. Cannot be used simultaneously with force.zero.group.strength
force.zero.group.cv: Numeric indicating the coefficient of variation for the forced 0-group (all immature) length. Resulting lengths will be randomly generated from a normal distribution.
xlab: Character giving the x-axis label without unit
base_size: Base size parameter for ggplot. See ggtheme.
legend.position: Position of the ggplot legend as a character. See ggtheme.
...: Additional arguments passed to geom_density_ridges.

Value

Returns a ggplot2 or tibble depending on the plot argument showing the maturity ogives.

Details

The 95% confidence intervals for the mean 50% mature estimate are calculated using the glm function by default. This routine might not be optimal when zero group fish are added. Hence, the function contains an option to bootstrap confidence intervals using the same number of data than observations (i.e. excluding the added data from the number of randomly resampled rows). Adding an integer to the bootstrap.n argument turns on this feature. Note that the confidence intervals calculated this way tend to be narrower than the glm() confidence intervals.

Author

Mikko Vihtakari // Institute of Marine Research.

Examples

# Simple L50 plot
data(survey_ghl)
plot_maturity(survey_ghl, length = "length", maturity = "maturity")
#> Warning: Ignoring unknown parameters: `size`
#> $plot
#> Picking joint bandwidth of 1.21

#> 
#> $text
#> [1] "50% maturity at length (L50) based on logit regressions:\n54.784 cm. 95% confidence intervals: 52.852 - 56.787\n  Number of specimens: 64265.\n Confidence intervals estimated from the glm object."
#> 
#> $params
#>       mean   ci.min ci.max  sex intercept     slope     n
#> 1 54.78361 52.85249 56.787 both -5.755492 0.1050587 64265
#> 
# \donttest{
# Bootstrapped CIs are narrower than the glm ones
plot_maturity(survey_ghl, bootstrap.n = 10)
#> Warning: Ignoring unknown parameters: `size`
#> $plot
#> Picking joint bandwidth of 1.21

#> 
#> $text
#> [1] "50% maturity at length (L50) based on logit regressions:\n54.793 cm. 95% confidence intervals: 54.706 - 54.884\n  Number of specimens: 64265\n\n Confidence intervals estimated using 10 bootstrap replicates."
#> 
#> $params
#>       mean   ci.min  ci.max  sex intercept     slope     n
#> 1 54.79348 54.70635 54.8836 both -5.755492 0.1050587 64265
#> 

# A50 plot, split by sex
plot_maturity(survey_ghl, length = "age", length.unit = "years",
xlab = "Age", length.bin.width = 1, split.by.sex = TRUE)$plot
#> Picking joint bandwidth of 0.602


# Add juveniles
plot_maturity(survey_ghl, length = "age", length.unit = "years",
xlab = "Age", length.bin.width = 1, split.by.sex = TRUE,
force.zero.group.length = 0,
force.zero.group.strength = 100)$plot
#> Picking joint bandwidth of 0.638

# }