predict.femlm: Predict method for femlm fits

In FENmlm: Fixed Effects Nonlinear Maximum Likelihood Models

Predict method for femlm fits

Description

This function obtains prediction from a fitted model estimated with femlm.

Usage

## S3 method for class 'femlm'
predict(object, newdata, type = c("response", "link"),
  ...)

Arguments

object	An object of class femlm. Typically the result of a femlm estimation.
newdata	A data.frame containing the variables used to make the prediction. If not provided, the fitted expected (or linear if type = "link") predictors are returned.
type	Character either equal to "response" (default) or "link". If type="response", then the output is at the level of the response variable, i.e. it is the expected predictor E(Y|X). If "link", then the output is at the level of the explanatory variables, i.e. the linear predictor X\cdot \beta.
...	Not currently used.

Value

It returns a numeric vector of length equal to the number of observations in argument newdata.

Author(s)

Laurent Berge

See Also

femlm, update.femlm, summary.femlm, vcov.femlm, getFE.

Examples

# Estimation on iris data
res = femlm(Sepal.Length ~ Petal.Length | Species, iris)

# what would be the prediction if the data was all setosa?
newdata = data.frame(Petal.Length = iris$Petal.Length, Species = "setosa")
pred_setosa = predict(res, newdata = newdata)

# Let's look at it graphically
plot(c(1, 7), c(3, 11), type = "n", xlab = "Petal.Length",
     ylab = "Sepal.Length")

newdata = iris[order(iris$Petal.Length), ]
newdata$Species = "setosa"
lines(newdata$Petal.Length, predict(res, newdata))

# versicolor
newdata$Species = "versicolor"
lines(newdata$Petal.Length, predict(res, newdata), col=2)

# virginica
newdata$Species = "virginica"
lines(newdata$Petal.Length, predict(res, newdata), col=3)

# The original data
points(iris$Petal.Length, iris$Sepal.Length, col = iris$Species, pch = 18)
legend("topleft", lty = 1, col = 1:3, legend = levels(iris$Species))

FENmlm documentation built on Aug. 22, 2023, 5:11 p.m.