| prediction.frame {memisc} | R Documentation |
prediction.frame produces a data frame that contains
the independent variables of a model together with model generated predictions.
## Default S3 method: prediction.frame(object,newdata=NULL,...,residuals=NULL)
object |
a model object from which predictions are generated. |
newdata |
an optional data frame for out-of-sample predictions. |
... |
further arguments passed to predict. |
residuals |
a character vector that specifies residuals that are added to the resulting data frame. |
A data frame.
lm1 <- lm(sr ~ pop15 + pop75 + dpi + ddpi, data = LifeCycleSavings)
lm2 <- lm(sr ~ pop15 + pop75 + dpi + ddpi + pop15*dpi, data = LifeCycleSavings)
str(prediction.frame(lm1))
str(prediction.frame(lm1, se.fit=TRUE))
str(prediction.frame(lm1, interval="prediction"))
str(prediction.frame(lm1, type="terms"))
str(prediction.frame(lm1,
se.fit=TRUE,
type="terms"))
str(prediction.frame(lm1,
se.fit=TRUE,
type="terms",
residuals="working"))
str(prediction.frame(lm1,
se.fit=TRUE,
type="terms",
residuals="partial"))
str(prediction.frame(lm2,
se.fit=TRUE,
type="terms",
residuals="partial"))
berkeley <- aggregate(wtable(Admit,Freq)~.,data=UCBAdmissions)
berk2 <- glm(cbind(Admitted,Rejected)~Gender+Dept,data=berkeley,family="binomial")
str(prediction.frame(berk2,
se.fit=TRUE,
type="terms",
residuals="partial"))