View source: R/plotmethod_lcc.R
| lccPlot | R Documentation | 
lcc ObjectThis function generates a plot of predictions versus the time covariate for 
an lcc object. Predicted values are connected by lines, while actual 
observations are denoted by circles. If components=TRUE was used in the 
lcc object, individual plots for each statistic (LCC, LPC, and LA) are 
produced on separate pages.
lccPlot(obj, type = "lcc", control = list(), ...)
obj | 
 An object inheriting from class "lcc", representing a fitted lcc model.  | 
type | 
 Character string specifying the type of plot to generate. 
  | 
control | 
 A list of graphical control values or character strings returned 
by the   | 
... | 
 Additional arguments passed to the 
  | 
An object of class ggplot or viewport, depending on the 
all.plot setting in control.
Thiago de Paula Oliveira, thiago.paula.oliveira@alumni.usp.br
lcc, plotControl
data(hue)
# Second degree polynomial model with random intercept, slope and quadratic term
fm1 <- lcc(data = hue, subject = "Fruit", resp = "H_mean",
          method = "Method", time = "Time", qf = 2, qr = 2, components = TRUE)
lccPlot(fm1, type = "lcc")
lccPlot(fm1, type = "lpc")
lccPlot(fm1, type = "la")
# Using ggplot2 themes
lccPlot(fm1, type = "lpc") + theme_bw() + labs(x = "Time (Days)", y = "LPC Value")
# Generating and saving plots
## Not run: 
  ggsave("lccPlot.pdf", lccPlot(fm1, type = "lcc"))
## End(Not run)
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