This function can be used to create a list containing the default options and arguments used by the plot functions.
saemix.plot.setoptions(saemixObject)
saemix.data.setoptions(saemix.data)
replace.plot.options(plot.opt, ...)
replace.data.options(plot.opt, ...)an object returned by the saemix function
an SaemixData object returned by the read.saemixData function
current graphic options
optional arguments passed to the plots, which will be used to override the current options defined in plot.opt
A list containing the options set at their default value. This list can be stored in an object and its elements modified to provide suitable graphs.
A more detailed description of the options set via these lists is provided in the PDF documentation. The "replace" functions are helper functions used within the plot functions. saemix.plot.setoptions has more available options than saemix.data.setoptions since it applies to all possible plots while the latter only applies to data.
Color of the lines added to the plots (default: "DarkRed")
Type of the lines added to the plots. Defaults to 2 (dashed line)
Width of the lines added to the plots (default: 2)
A logical value. If TRUE, users will be prompted before each new plot. Defaults to FALSE
A numerical value giving the amount by which plotting text and symbols should be magnified relative to the default. Defaults to 1 (no magnification)
Magnification to be used for axis annotation relative to the current setting of 'cex'. Defaults to 1 (no magnification)
Magnification to be used for main titles relative to the current setting of 'cex'. Defaults to 1 (no magnification)
Magnification to be used for x and y labels relative to the current setting of 'cex'. Defaults to 1 (no magnification)
For the VPC plots: color filling the prediction interval for the median. Defaults to "pink"
For the VPC plots: color filling the prediction interval for the limits of the prediction interval. Defaults to "slategray1"
For the VPC plots: color of the line showing the median of the simulated data. Defaults to "indianred4"
For the VPC plots: color of the lines showing the median, 2.5 and 97.5th percentiles (for a 95
For the VPC plots: color of the line showing the boundaries of the prediction intervals. Defaults to "slategray4"
For the VPC plots: color used to plot the observations. Defaults to "steelblue4"
Name of the covariate to be used in the plots. Defaults to the first covariate in the model
Value of the covariate to be used in the plots. Defaults to NA, indicating that the median value of the covariate (for continuous covariates) or the reference category (for categorical covariates) will be used
List of indices of subjects to be included in the individual plots (defaults to all subjects)
a string, giving the type of the individual estimates ("map"= conditional mode, "eap"=conditional mean). Defaults to conditional mode
Main line color (default: black)
Type of smoothing when a smoothed line is used in the plot ("m": mean value, "l": linear regression; "s": natural splines). Several options may be combined, for instance "ls" will add both a linear regression line and a line representing the fit of a natural spline. Defaults to "s"
Line type. Defaults to 1, corresponding to a straight line
For the VPC plots: type of the line showing the median of the simulated data. Defaults to 2 (dashed)
For the VPC plots: type of the line showing the observed data. Defaults to 1
For the VPC plots: type of the line showing the boundaries of the simulated data. Defaults to 2 (dashed)
Line width (default: 1)
For the VPC plots: thickness of the line showing the median of the simulated data. Defaults to 2
For the VPC plots: thickness of the line showing the median and boundaries of the observed data. Defaults to 2
For the VPC plots: thickness of the line showing the boundaries of the simulated data. Defaults to 1
Name of the parameter to be used in the plots. Defaults to the first parameter in the model
Symbol type. Defaults to 20, corresponding to small dots
Main symbol color (default: black)
Range (expressed in number of SD) over which to plot the marginal distribution. Defaults to 4, so that the random effects for the marginal distribution is taken over the range [-4 SD; 4 SD]
Type of residual plot ("res.vs.x": scatterplot versus X, "res.vs.pred": scatterplot versus predictions, "hist": histogram, "qqplot": QQ-plot) (default: "res.vs.x")
When TRUE, smoothed lines are added in the plots of predictions versus observations (default: FALSE)
Title of the graph (default: none)
Type of the plot (as in the R plot function. Defaults to "b", so that both lines and symbols are shown
Name of the predictor used in the plots (X). Defaults to the name of the first predictor in the model (saemix.data$names$predictors[1])
Number of binning intervals when plotting the VPC (the (vpc.bin-1) breakpoints are taken as the empirical quantiles of the X data). Defaults to 10
Size of the prediction intervals.Defaults to 0.95 for the 95% prediction interval
Should the observations be overlayed on the VPC plot. Defaults to TRUE
Should prediction bands be computed around the median and the bounds of the prediction intervals for the VPC. Defaults to TRUE
Label for the X-axis. Defaults to the name of the X predictor followed by the unit in bracket (eg "Time (hr)")
Range for the X-axis. Defaults to NA, indicating that the range is to be set by the plot function
A logical value. If TRUE, a logarithmic scale is in use. Defaults to FALSE
Name of the predictor used in the plots (X)
Label for the Y-axis. Defaults to the name of the response followed by the unit in bracket (eg "Concentration (mg/L)" (Default: none)
Range for the Y-axis. Defaults to NA, indicating that the range is to be set by the plot function
A logical value. If TRUE, a logarithmic scale is in use. Defaults to FALSE
if TRUE, plots separate plots for each individual, otherwise plots a spaghetti plot of all the data. Defaults to FALSE
for individual plots, plots only a limited number of subjets (nmax). Defaults to TRUE
for individual plots, when limit is TRUE, the maximum number of plots to produce. Defaults to 12
for individual plots, if TRUE, randomly samples nmax different subjects to plot. Defaults to FALSE (the first nmax subjects are used in the plots)
Kuhn E, Lavielle M. Maximum likelihood estimation in nonlinear mixed effects models. Computational Statistics and Data Analysis 49, 4 (2005), 1020-1038.
Comets E, Lavenu A, Lavielle M. SAEMIX, an R version of the SAEM algorithm. 20th meeting of the Population Approach Group in Europe, Athens, Greece (2011), Abstr 2173.
SaemixObject,saemix, saemix.plot.data, saemix.plot.convergence, saemix.plot.llis, saemix.plot.randeff, saemix.plot.obsvspred, saemix.plot.fits, saemix.plot.parcov, saemix.plot.distpsi, saemix.plot.scatterresiduals, saemix.plot.vpc
# NOT RUN {
# Theophylline example, after a call to fit.saemix (see examples)
# Not run
# sopt<-saemix.plot.setoptions(saemix.fit)
# sopt$ask<-TRUE
# }
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