R: Fix mean parameters in 'lvm'-object

intercept {lava} | R Documentation

## 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) = α_1 + β_1 X

E(Y_2|X) = α_2 + β_2 X

defined by the call

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

To fix α_1=α_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 α_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)

[Package lava version 1.6.1 Index]