predict.lvm: Prediction in structural equation models

In kkholst/lava: Latent Variable Models

Prediction in structural equation models

Description

Prediction in structural equation models

Usage

## S3 method for class 'lvm'
predict(
  object,
  x = NULL,
  y = NULL,
  residual = FALSE,
  p,
  data,
  path = FALSE,
  quick = is.null(x) & !(residual | path),
  ...
)

Arguments

object	Model object
x	optional list of (endogenous) variables to condition on
y	optional subset of variables to predict
residual	If true the residuals are predicted
p	Parameter vector
data	Data to use in prediction
path	Path prediction
quick	If TRUE the conditional mean and variance given covariates are returned (and all other calculations skipped)
...	Additional arguments to lower level function

See Also

predictlvm

Examples

m <- lvm(list(c(y1,y2,y3)~u,u~x)); latent(m) <- ~u
d <- sim(m,100)
e <- estimate(m,d)

## Conditional mean (and variance as attribute) given covariates
r <- predict(e)
## Best linear unbiased predictor (BLUP)
r <- predict(e,vars(e))
##  Conditional mean of y3 giving covariates and y1,y2
r <- predict(e,y3~y1+y2)
##  Conditional mean  gives covariates and y1
r <- predict(e,~y1)
##  Predicted residuals (conditional on all observed variables)
r <- predict(e,vars(e),residual=TRUE)

kkholst/lava documentation built on Feb. 22, 2024, 4:07 p.m.