Description Usage Arguments Details Value Author(s) References See Also Examples
Make predictions based on a fitted "compCL"
object.
1 2 |
object |
fitted |
Znew |
|
Zcnew |
|
s |
value(s) of the penalty parameter |
... |
not used. |
s
is the vector at which predictions are requested. If s
is not in the lambda
sequence used for fitting the model, the predict
function uses linear interpolation.
predicted values at the requested values of s
.
Zhe Sun and Kun Chen
Lin, W., Shi, P., Peng, R. and Li, H. (2014) Variable selection in regression with compositional covariates, https://academic.oup.com/biomet/article/101/4/785/1775476. Biometrika 101 785-979.
compCL
and coef
,
predict
and plot
methods
for "compCL"
object.
1 2 3 4 5 6 | Comp_data = comp_Model(n = 50, p = 30)
Comp_data2 = comp_Model(n = 30, p = 30, beta = Comp_data$beta)
m1 = compCL(y = Comp_data$y, Z = Comp_data$X.comp,
Zc = Comp_data$Zc, intercept = Comp_data$intercept)
predict(m1, Znew = Comp_data2$X.comp, Zcnew = Comp_data2$Zc)
predict(m1, Znew = Comp_data2$X.comp, Zcnew = Comp_data2$Zc, s = c(1, 0.5, 0.1))
|
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