Model Predictions for a Linear Model
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.)
predict20x(object, newdata, cilevel = 0.95, digit = 3, print.out = TRUE, ...)
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'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.
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.
This function is deprecated. It will be removed in future versions of the package.
this function is deprecated as it is never used in class any more. We prefer the standard predict method.
# 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)
predict, predict.lm, as.data.frame.