Model Predictions
Predict is a generic function with, at present, a single method for "lm" objects,
Predict.lm, which is a modification of the standard predict.lm method in
the stats package, but with an additional vcov. argument for a user-specified covariance matrix for intreval estimation.
Predict(object, ...)
## S3 method for class 'lm'
Predict(object, newdata, se.fit = FALSE,
scale = NULL, df = Inf,
interval = c("none", "confidence", "prediction"),
level = 0.95, type = c("response", "terms"),
terms = NULL, na.action = na.pass,
pred.var = res.var/weights, weights = 1, vcov., ...)object |
a model object for which predictions are desired. |
newdata, se.fit, scale, df, interval, level, type, terms, na.action, pred.var, weights |
see |
vcov. |
optional, either a function to compute the coefficient covariance matrix of
|
... |
arguments to pass down to |
If there is no appropriate method for Predict, then a predict method
is invoked. If there is a specific predict method for the primary class of object but
only an inherited Predict method, then the predict method is invoked.
Thus an object of class c("glm", "lm") will invoke method predict.glm rather than
Predict.lm, but an object of class c("aov", "lm") will invoke Predict.lm
rather than predict.lm.
See predict and predict.lm.
John Fox jfox@mcmaster.ca
Fox, J. and Weisberg, S. (2019) An R Companion to Applied Regression, Third Edition, Sage.
mod <- lm(interlocks ~ log(assets), data=Ornstein) newd <- data.frame(assets=exp(4:12)) (p1 <- predict(mod, newd, interval="prediction")) p2 <- Predict(mod, newd, interval="prediction", vcov.=vcov) all.equal(p1, p2) # the same (predict(mod, newd, se=TRUE)) (p3 <- Predict(mod, newd, se=TRUE, vcov.=hccm)) # larger SEs p4 <- Predict(mod, newd, se=TRUE, vcov.=hccm(mod, type="hc3")) all.equal(p3, p4) # the same
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