prep.matrixDynamics {dynr} R Documentation

## Recipe function for creating Linear Dynamcis using matrices

### Description

Recipe function for creating Linear Dynamcis using matrices

### Usage

prep.matrixDynamics(params.dyn = NULL, values.dyn, params.exo = NULL,
values.exo = NULL, params.int = NULL, values.int = NULL, covariates,
isContinuousTime)


### Arguments

 params.dyn the matrix of parameter names for the transition matrix in the specified linear dynamic model values.dyn the matrix of starting/fixed values for the transition matrix in the specified linear dynamic model params.exo the matrix of parameter names for the regression slopes of covariates on the latent variables (see details) values.exo matrix of starting/fixed values for the regression slopes of covariates on the latent variables (see details) params.int vector of names for intercept parameters in the dynamic model specified as a matrix or list of matrices. values.int vector of intercept values in the dynamic model specified as matrix or list of matrices. Contains starting/fixed values of the intercepts. covariates the names or the index numbers of the covariates used in the dynamic model isContinuousTime logical. When TRUE, use a continuous time model. When FALSE use a discrete time model.

### Details

A recipe function for specifying the deterministic portion of a set of linear dynamic functions as:

Discrete-time model: eta(t+1) = int + dyn*eta(t) + exo*x(t), where eta(t) is a vector of latent variables, x(t) is a vector of covariates, int, dyn, and exo are vectors and matrices specified via the arguments *.int, *.dyn, and *.exo.

Continuous-time model: d/dt eta(t) = int + dyn*eta(t) + exo*x(t), where eta(t) is a vector of latent variables, x(t) is a vector of covariates, int, dyn, and exo are vectors and matrices specified via the arguments *.int, *.dyn, and *.exo.

The left-hand side of the dynamic model consists of a vector of latent variables for the next time point in the discrete-time case, and the vector of derivatives for the latent variables at the current time point in the continuous-time case.

For models with regime-switching dynamic functions, the user will need to provide a list of the *.int, *.dyn, and *.exo arguments. (when they are specified to take on values other than the default of zero vectors and matrices), or if a single set of vectors/matrices are provided, the same vectors/matrices are assumed to hold across regimes.

prep.matrixDynamics serves as an alternative to prep.formulaDynamics.

### Value

Object of class 'dynrDynamicsMatrix'

### See Also

Methods that can be used include: print, show

### Examples

#Single-regime, continuous-time model. For further details run:
#demo(RSNonlinearDiscrete, package="dynr"))
dynamics <- prep.matrixDynamics(
values.dyn=matrix(c(0, -0.1, 1, -0.2), 2, 2),
params.dyn=matrix(c('fixed', 'spring', 'fixed', 'friction'), 2, 2),
isContinuousTime=TRUE)

#Two-regime, continuous-time model. For further details run:
#demo(RSNonlinearDiscrete, package="dynr"))
dynamics <- prep.matrixDynamics(
values.dyn=list(matrix(c(0, -0.1, 1, -0.2), 2, 2),
matrix(c(0, -0.1, 1, 0), 2, 2)),
params.dyn=list(matrix(c('fixed', 'spring', 'fixed', 'friction'), 2, 2),
matrix(c('fixed', 'spring', 'fixed', 'fixed'), 2, 2)),
isContinuousTime=TRUE)


[Package dynr version 0.1.16-27 Index]