predict_smooth: Predictions from model
In mgss: A Matrix-Free Multigrid Preconditioner for Spline Smoothing
Description
Usage
Arguments
Value
Examples
Description
Makes predictions of new observations from a fitted spline model.
Usage
1
predict_smooth(model_smooth, X)
Arguments
model_smooth
A spline model resulting from CG_smooth, PCG_smooth, or MGCG_smooth.
X
Matrix containing the new observations.
Value
Vector of length nrow(X) of predictions.
Examples
1
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3
4
5
6
data <- generate_test_data(100, 2)
X <- data$X_train
y <- data$y_train
result <- PCG_smooth(m = c(7,7), q = c(3,3), lambda = 0.1, X = X, y = y, print_error = FALSE)
X_test <- data$X_test
predict_smooth(model_smooth = result, X = X_test)
mgss documentation built on May 10, 2021, 9:07 a.m.
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Description Usage Arguments Value Examples
Description
Makes predictions of new observations from a fitted spline model.
Usage
1 | predict_smooth(model_smooth, X)
|
Arguments
model_smooth |
A spline model resulting from |
X |
Matrix containing the new observations. |
Value
Vector of length nrow(X) of predictions.
Examples
1 2 3 4 5 6 | data <- generate_test_data(100, 2)
X <- data$X_train
y <- data$y_train
result <- PCG_smooth(m = c(7,7), q = c(3,3), lambda = 0.1, X = X, y = y, print_error = FALSE)
X_test <- data$X_test
predict_smooth(model_smooth = result, X = X_test)
|
R Package Documentation
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We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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