Fix mean parameters in 'lvm'-object
Define linear constraints on intercept parameters in a lvm-object.
## S3 replacement method for class 'lvm' intercept(object, vars, ...) <- value
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
|
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.
A lvm-object
Variables will be added to the model if not already present.
Klaus K. Holst
## 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)
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