stepwise {chemometrics} | R Documentation |
Stepwise regression, starting from the empty model, with scope to the full model
stepwise(formula, data, k, startM, maxTime = 1800, direction = "both", writeFile = FALSE, resname = "stepres00", maxsteps = 500, ...)
formula |
formula, like y~X, i.e., dependent~response variables |
data |
data frame to be analyzed |
k |
sensible values are log(nrow(x)) for BIC or 2 for AIC; if not provided -> BIC |
startM |
optional, the starting model |
maxTime |
maximal time to be used for algorithm |
direction |
either "forward" or "backward" or "both" |
writeFile |
if TRUE results are stored in the file "resname" |
resname |
filename where results are stored, only if writeFile is TRUE |
maxsteps |
maximum number of steps |
... |
additional plot arguments |
This function is similar to the function step
for stepwise regression.
It is especially designed for cases where the number of regressor variables is much
higher than the number of objects. The formula for the full model (scope) is automatically
generated.
usedTime |
time that has been used for algorithm |
bic |
BIC values for different models |
models |
matrix with no. of models rows and no. of variables columns, and 0/1 entried defining the models |
Leonhard Seyfang and (marginally) Peter Filzmoser <P.Filzmoser@tuwien.ac.at>
K. Varmuza and P. Filzmoser: Introduction to Multivariate Statistical Analysis in Chemometrics. CRC Press. To appear.
data(yarn) res=stepwise(density~NIR,data=yarn,maxsteps=2) # increase maxsteps to get a good solution