PSM.plot: Basic plots of data and output

In PSM: Non-Linear Mixed-Effects modelling using Stochastic Differential Equations.

Description

Create basic plots of data and state estimates in PSM.

Usage

  PSM.plot(Data, Smooth = NULL, indiv = NULL, type = NULL)

Arguments

Data	Data list, see description in PSM.estimate.
Smooth	Output from PSM.smooth.
indiv	A vector of integers with which individuals to include.
type	A vector of strings listing the types of plots to create. The possibilities are: ‘Y’ Observations ‘U’ Input ‘X’ Simulated states at sample times ‘longX’ Simulated states with time increment deltaTime ‘Xp’ Predicted states ‘Xf’ Filtered states ‘Xs’ Smoothed states ‘Yp’ Response based on predicted state ‘Ys’ Response based on smoothed state ‘Yp.Y’ As above with observations added ‘Ys.Y’ As above with observations added ‘res’ Residuals (Y-Yp) ‘acf’ Auto-correlation of residuals ‘eta’ Shows estimates of random effects in plot. If Smooth is not given it will show the value of simulated random effects if they are contained in Data. If a string is preceeded by ‘logx.’, ‘logy.’ or ‘logx.logy.’ the corresponding axis is shown on log-scale. An example is: type=c('Xs','logy.Ys.Y','res','eta')

Value

None (invisible NULL).

Note

For further details please also read the package vignette pdf-document by writing vignette("PSM") in R.

Author(s)

Stig B. Mortensen and S<f8>ren Klim

References

Please visit http://www.imm.dtu.dk/psm or refer to the help page for PSM.

See Also

PSM, PSM.estimate, PSM.smooth, PSM.simulate, PSM.template

Examples

cat("\nExamples are included in the package vignette.\n")

PSM documentation built on May 2, 2019, 6:53 p.m.