ClusterVAR (version 0.0.8)

coef.ClusterVAR: Show coefficients of given Model

Description

Extracts the coefficients of a given model from the output object of the LCVAR function.

Usage

# S3 method for ClusterVAR
coef(object, Model,...)

Value

Lags

An integer vector specifying for which model the coefficients are shown. For example, Lags = c(1,1,2) indicates a model with three clusters, in which the first cluster has one lag, the second cluster has 1 lag, and the third cluster has 2 lags.

Classification

The crisp classification for each individual into a cluster. Crisp classifications are made based on an individual's modal cluster membership probabilities.

VAR_coefficients

The cluster-wise vector-autoregressive coefficients for each cluster.

Exogenous_coefficients

The cluster-wise exogenous coefficients for each cluster. The first column in each array indicates the (conditional) within-person mean in that cluster. If exogenous variable(s) were specified, the other columns indicate the influences of the exogenous variable(s) in that cluster.

Sigma

The cluster-wise innovation covariance matrix for each cluster.

Proportions

The mixing proportions for each cluster. These can be considered as the proportion of individuals belonging to the respective cluster.

PredictableTimepoints

The total number of time-points in this dataset that could be predicted because the previous time-point(s) were observed. In case of unequal lags across different clusters, the number of time-points for each person are weighted by their posterior cluster-membership probability. See also numberPredictableObservations().

Converged

A logical value that indicates whether this model converged.

Arguments

object

An output object of the LCVAR function.

Model

An integer vector specifying the model for which coefficients should be shown. For example, Model = c(1,1,2) returns the coefficients of a model with three clusters (i.e., latent classes), in which the first cluster has one lag, the second cluster has 1 lag, and the third cluster has 2 lags. The vector length indicates the number of clusters in the model of interest.

...

Pass additional arguments.

Author

Anja Ernst & Jonas Haslbeck

Examples

# \donttest{
LCVAR_outExample <- LCVAR(Data = ExampleData,
                           yVars = 1:4, ID = 5, Beep = 6,
                           xContinuous = 7, xFactor = 8,
                           Clusters = 2, Lags = 1:2, smallestClN = 3,
                           Cores = 2, RndSeed = 3, Rand = 2,
                           it = 25)

coef(LCVAR_outExample, Model = c(1, 1))
coef(LCVAR_outExample, Model = c(2, 2))
# }