1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
|
\name{mkinerrplot}
\alias{mkinerrplot}
\title{
Function to plot squared residuals and the error model for an mkin object
}
\description{
This function plots the squared residuals for the specified subset of the
observed variables from an mkinfit object. In addition, one or more
dashed line(s) show the fitted error model.
A combined plot of the fitted model and this error model plot can be
obtained with \code{\link{plot.mkinfit}}
using the argument \code{show_errplot = TRUE}.
}
\usage{
mkinerrplot(object,
obs_vars = names(object$mkinmod$map),
xlim = c(0, 1.1 * max(object$data$predicted)),
xlab = "Predicted", ylab = "Squared residual",
maxy = "auto", legend= TRUE, lpos = "topright",
col_obs = "auto", pch_obs = "auto",
...)
}
\arguments{
\item{object}{
A fit represented in an \code{\link{mkinfit}} object.
}
\item{obs_vars}{
A character vector of names of the observed variables for which residuals
should be plotted. Defaults to all observed variables in the model
}
\item{xlim}{
plot range in x direction.
}
\item{xlab}{
Label for the x axis.
}
\item{ylab}{
Label for the y axis.
}
\item{maxy}{
Maximum value of the residuals. This is used for the scaling of
the y axis and defaults to "auto".
}
\item{legend}{
Should a legend be plotted?
}
\item{lpos}{
Where should the legend be placed? Default is "topright". Will be passed on to
\code{\link{legend}}.
}
\item{col_obs}{
Colors for the observed variables.
}
\item{pch_obs}{
Symbols to be used for the observed variables.
}
\item{\dots}{
further arguments passed to \code{\link{plot}}.
}
}
\value{
Nothing is returned by this function, as it is called for its side effect, namely to produce a plot.
}
\author{
Johannes Ranke
}
\seealso{
\code{\link{mkinplot}}, for a way to plot the data and the fitted lines of the
mkinfit object. }
\examples{
\dontrun{
model <- mkinmod(parent = mkinsub("SFO", "m1"), m1 = mkinsub("SFO"))
fit <- mkinfit(model, FOCUS_2006_D, error_model = "tc", quiet = TRUE)
mkinerrplot(fit)
}
}
\keyword{ hplot }
|
