intercept: Fix mean parameters in 'lvm'-object

In lava: Latent Variable Models

Fix mean parameters in 'lvm'-object

Description

Define linear constraints on intercept parameters in a lvm-object.

Usage

## S3 replacement method for class 'lvm'
intercept(object, vars, ...) <- value

Arguments

object	lvm-object
...	Additional arguments
vars	character vector of variable names
value	Vector (or list) of parameter values or labels (numeric or character) or a formula defining the linear constraints (see also the regression or covariance methods).

Details

The intercept function is used to specify linear constraints on the intercept parameters of a latent variable model. As an example we look at the multivariate regression model

E(Y_1|X) = \alpha_1 + \beta_1 X

E(Y_2|X) = \alpha_2 + \beta_2 X

defined by the call

m <- lvm(c(y1,y2) ~ x)

To fix \alpha_1=\alpha_2 we call

intercept(m) <- c(y1,y2) ~ f(mu)

Fixed parameters can be reset by fixing them to NA. For instance to free the parameter restriction of Y_1 and at the same time fixing \alpha_2=2, we call

intercept(m, ~y1+y2) <- list(NA,2)

Calling intercept with no additional arguments will return the current intercept restrictions of the lvm-object.

Value

A lvm-object

Note

Variables will be added to the model if not already present.

Author(s)

Klaus K. Holst

See Also

covariance<-, regression<-, constrain<-, parameter<-, latent<-, cancel<-, kill<-

Examples

## A multivariate model
m <- lvm(c(y1,y2) ~ f(x1,beta)+x2)
regression(m) <- y3 ~ f(x1,beta)
intercept(m) <- y1 ~ f(mu)
intercept(m, ~y2+y3) <- list(2,"mu")
intercept(m) ## Examine intercepts of model (NA translates to free/unique paramete##r)

lava documentation built on Nov. 5, 2023, 1:10 a.m.