Description Usage Arguments Details Value Author(s) References See Also Examples
Predictions from a sparse partial robust M regression model.
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object |
object of class sprm. |
newdata |
optional data frame with new observations. |
... |
further arguments. Currently not used. |
If newdata
is specified the sprm model is used to predict the fitted values for this data set, otherwise the fitted values of the model are returned.
predict.sprm
returns a vector of the predicted response.
Sven Serneels, BASF Corp and Irene Hoffmann
Hoffmann, I., Serneels, S., Filzmoser, P., Croux, C. (2015). Sparse partial robust M regression. Chemometrics and Intelligent Laboratory Systems, 149, 50-59.
Serneels, S., Croux, C., Filzmoser, P., Van Espen, P.J. (2005). Partial Robust M-Regression. Chemometrics and Intelligent Laboratory Systems, 79, 55-64.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | set.seed(5023)
U1 <- c(rep(2,20), rep(5,30))
U2 <- rep(3.5,50)
X1 <- replicate(5, U1+rnorm(50))
X2 <- replicate(20, U2+rnorm(50))
X <- cbind(X1,X2)
beta <- c(rep(1, 5), rep(0,20))
e <- c(rnorm(45,0,1.5),rnorm(5,-20,1))
y <- X%*%beta + e
d <- as.data.frame(X)
d$y <- y
smod <- sprms(y~., data=d, a=1, eta=0.5, fun="Hampel")
dnew <- as.data.frame(cbind(replicate(5, U1+rnorm(10)), replicate(20, U2+rnorm(10))))
ynewp <- predict(smod, newdata=dnew)
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