plot_boot_vec: Plot stochastic vectors

In nikolaifish/bamExtras: Functions and Data in Support of Stock Assessments with the Beaufort Assessment Model (BAM)

Plot stochastic vectors

Description

Plot median values and confidence intervals (shaded region) for stochastic (e.g. bootstrapped) vectors.

Usage

plot_boot_vec(
  data,
  CIpct = 95,
  runsToKeep = NULL,
  ref_x = NULL,
  ref_y = NULL,
  col_lines = rgb(0, 0, 0, 1),
  col_shade = NULL,
  add = FALSE,
  ...
)

Arguments

data	a numeric matrix or data frame that can be coerced to a numeric matrix where rows are runs and columns represent a numeric sequence (e.g. age, year). Note that the function would probably work for any numeric matrix, but it's intended for bootstrapped time- or age-series data.
CIpct	percentage to define the range of the confidence intervals to plot
runsToKeep	optional vector of integer values corresponding to the rows of data to include in the plot
ref_x, ref_y	x and y vectors for adding a reference line to the plot (e.g. base run values)
col_lines	color for lines depicting central tendency and confidence limits. Expects hex color
col_shade	color for shading confidence bands
add	logical. Should a new plot be drawn or should it be added to an existing plot?
...	other arguments to pass to matplot

Author(s)

Nikolai Klibansky

Examples

## Not run: 
bootData <- t(replicate(n=100,random_walk(mu=0.5)))
plot_boot_vec(bootData)

## End(Not run)

nikolaifish/bamExtras documentation built on July 21, 2023, 8:26 a.m.