# intercept: Fix mean parameters in 'lvm'-object In lava: Latent Variable Models

## Description

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

## Usage

 ```1 2``` ```## 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

## Author(s)

Klaus K. Holst

`covariance<-`, `regression<-`, `constrain<-`, `parameter<-`, `latent<-`, `cancel<-`, `kill<-`
 ```1 2 3 4 5 6``` ```## 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) ```