predict[.lm](object, newdata = model.frame(object), se.fit = FALSE, scale = NULL, df = Inf, interval = c("none", "confidence", "prediction"), level = 0.95)
predict.lm
produces predicted values, obtained by evaluating
the regression function in the frame newdata
. If the logical
se.fit
is TRUE
, standard errors of the predictions are
calculated. If the numeric argument scale
is set (with optional
df
), it is used as the residual standard deviation in the
computation of the standard errors, otherwise this is extracted from
the model fit. Setting intervals
specifies computation of
confidence or prediction (tolerance) intervals at the specified
level
.predict.lm
produces a vector of predictions or a matrix of
predictions and bounds with column names fit
, lwr
, and
upr
if interval
is set. If se.fit
is
TRUE
, a list with the following components is returned
fit
| vector or matrix as above |
se.fit
| standard error of predictions |
residual.scale
| residual standard deviations |
df
| degrees of freedom for residual |
lm
, predict
.## Predictions x <- rnorm(15) y <- x + rnorm(15) predict(lm(y ~ x)) predict(lm(y ~ x), data.frame(x = seq(-3, 3, 0.1)), se = TRUE)