View source: R/growthrate_gam.R
| gam_growthrate_plot | R Documentation | 
plot output of growthrate_gam and list for gam_growthrate_plot_combine
gam_growthrate_plot(
  d,
  model,
  ci,
  agevar,
  idvar = NULL,
  yvar = as.character(model$formula[2]),
  plotsavename = NA,
  xplotname = "Age",
  yplotname = yvar,
  draw_maturation = T,
  draw_points = T,
  show_all_fill = F,
  ci_plot = T
)
| d | dataframe model was built on (for actual points) | 
| model | gam model (for predicted line) | 
| ci | growthrate_gam output (confidence interval and derivitive) | 
| agevar | column name of age var e.g. 'Ageatvisit' | 
| idvar | line grouping var e.g., 'lunaid', set to NULL if no random effect in model | 
| yvar | model yvar e.g. 'f1score', default pulled from model formula | 
| plotsavename | PDF output name e.g. 'growth.pdf', not saved when NA, not ploted when NULL | 
| xplotname | 'Age' | 
| yplotname | 'f1score', default is yvar (model yvar) | 
| draw_maturation | T|F, show dotted line on first maturation point | 
| draw_points | T|F, show individual points as scatter plot over gam fit line | 
| show_all_fill | T|F, should we clip the raster fill to only significant ages? | 
| ci_plot | T|F, plot 95 percent confidence interval with geom_ribbon? | 
 # no random effects
 m <- mgcv::gam(f1score ~ s(Ageatvisit), data=d)
 ci <- gam_growthrate(m, 'Ageatvisit')
 gam_growthrate_plot(d, m, ci, 'Ageatvisit')
 # w/random effects 'id'
 m <- mgcv::gam(f1score ~ s(Ageatvisit) + s(visit) + s(id, bs="re"), data=d)
 ci <- gam_growthrate(m, 'Ageatvisit')
 gam_growthrate_plot(d, m, ci, 'Ageatvisit', 'id')
 # replot example, see gam_growthrate_plot_combine
 mod <- mgcv::gam(conc~s(uptake), data=CO2)
 ci <- LNCDR::gam_growthrate(mod, 'uptake', n = 10000, qnt = c(0.025, 0.975))
 plist <- gam_growthrate_plot(cars, mod, ci, 'uptake', xplotname='uptake')
 plist$ageplot <- plist$ageplot + xlab('foobar')
 gam_growthrate_plot_combine(plist$ageplot, plist$tile)
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