plot.mpm_df: plot

In ianjonsen/foieGras: Fit Continuous-Time State-Space and Latent Variable Models for Quality Control of Argos Satellite (and Other) Telemetry Data and for Estimating Changes in Animal Movement

plot

Description

visualize fits from an mpm object

Usage

## S3 method for class 'mpm_df'
plot(
  x,
  y = NULL,
  se = FALSE,
  pages = 0,
  ncol = 1,
  ask = TRUE,
  pal = "Plasma",
  rev = FALSE,
  ...
)

Arguments

x	a aniMotum mpm fit object with class mpm_df
y	optional ssm fit object with class ssm_df corresponding to x. If absent, 1-d plots of gamma_t time series are rendered otherwise, 2-d track plots with locations coloured by 'gamma_t“ are rendered.
se	logical (default = FALSE); should points be scaled by gamma_t uncertainty (ignored if y is not supplied)
pages	plots of all individuals on a single page (pages = 1; default) or each individual on a separate page (pages = 0)
ncol	number of columns to use for faceting. Default is ncol = 1 but this may be increased for multi-individual objects. Ignored if pages = 0
ask	logical; if TRUE (default) user is asked for input before each plot is rendered. set to FALSE to return ggplot objects
pal	grDevices::hcl.colors palette to use (default: "Plasma"; see grDevices::hcl.pals for options)
rev	reverse colour palette (logical)
...	additional arguments to be ignored

Value

a ggplot object with either: 1-d time series of gamma_t estimates (if y not provided), with estimation uncertainty ribbons (95 % CI's); or 2-d track plots (if y provided) coloured by gamma_t, with smaller points having greater uncertainty (size is proportional to SE^-2, if se = TRUE). Plots can be rendered all on a single page (pages = 1) or on separate pages.

Examples

# generate a ssm fit object (call is for speed only)
xs <- fit_ssm(sese2, spdf=FALSE, model = "rw", time.step=72, control = ssm_control(verbose = 0))

# fit mpm to ssm fits
xm <- fit_mpm(xs, model = "jmpm")

# plot 1-D mp timeseries on 1 page
plot(xm, pages = 1)

ianjonsen/foieGras documentation built on Jan. 17, 2025, 11:15 p.m.