plot,dynrCook-method

dynrModel

The style of the plot in the first panel. If style is 1 (default), user-selected smoothed state variables are plotted. If style is 2, user-selected observed-versus-predicted values are plotted.

style

(optional) The names of the states to be plotted, which should be a subset of the state.names slot of the measurement slot of dynrModel.

names.state

(optional) The names of the observed variables to be plotted, which should be a subset of the obs.names slot of the measurement slot of dynrModel.

names.observed

A logical value indicating whether or not to plot the formulas for the dynamic model

printDyn

A logical value indicating whether or not to plot the formulas for the measurement model

printMeas

Dynamic modeling of all kinds in R. These include models of
processes in discrete time or continuous time. They also include processes
that are linear or nonlinear. Latent variables can be continuous (e.g. state
space models) or discrete (e.g. regime-switching models). The general approach
involves maximum likelihood estimation of single- and multi-subject models of
latent time series with the extended Kalman filter and Kim filter. The user
provides recipes and data which are combined into a model that is then cooked to
obtain free parameter estimates.

plot,dynrCook-method: Plot method for dynrCook objects

Description

Usage

Arguments

Details