predict.femlm {FENmlm} | R Documentation |
This function obtains prediction from a fitted model estimated with femlm
.
## S3 method for class 'femlm' predict(object, newdata, type = c("response", "link"), ...)
object |
An object of class |
newdata |
A data.frame containing the variables used to make the prediction. If not provided, the fitted expected (or linear if |
type |
Character either equal to |
... |
Not currently used. |
It returns a numeric vector of length equal to the number of observations in argument newdata
.
Laurent Berge
femlm
, update.femlm
, summary.femlm
, vcov.femlm
, getFE
.
# 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))