s20x (version 3.1-40)

predict20x: Model Predictions for a Linear Model

Description

Uses the main output and some error messages from R function 'predict' but gives you more output. (Error messages are not reliable when used in Splus.)

Usage

predict20x(object, newdata, cilevel = 0.95, digit = 3, print.out = TRUE, ...)

Value

frame

vector or matrix including predicted values, confidence intervals and predicted intervals.

fit

prediction values.

se.fit

standard error of predictions.

residual.scale

residual standard deviations.

df

degrees of freedom for residual.

cilevel

confidence level of the interval.

Arguments

object

an lm object, i.e. the output from lm.

newdata

prediction data frame.

cilevel

confidence level of the interval.

digit

decimal numbers after the point.

print.out

if TRUE, print out the prediction matrix.

...

optional arguments that are passed to the generic 'predict'

Details

Note: The data frame, newdata, must have the same column order and data types (e.g. numeric or factor) as those used in fitting the model.

See Also

predict, predict.lm, as.data.frame.

Examples

# Zoo data
data(zoo.df)
zoo.df = within(zoo.df, {day.type = factor(day.type)})
zoo.fit = lm(log(attendance) ~ time + sun.yesterday + nice.day + day.type + tv.ads,
             data = zoo.df)
pred.zoo = data.frame(time = 8, sun.yesterday = 10.8, nice.day = 0,
                      day.type = factor(3), tv.ads = 1.181)
predict20x(zoo.fit, pred.zoo)

# Peruvian Indians data
data(peru.df)
peru.fit = lm(BP ~ age + years + I(years^2) + weight + height, data = peru.df)
pred.peru = data.frame(age = 21, years = 2, `I(years^2)` = 2, weight = 71, height = 1629)
predict20x(peru.fit, pred.peru)