pred.sigcom: Prediction for linear function-on-function regression using...
In FRegSigCom: Functional Regression using Signal Compression Approach
Description
Usage
Arguments
Value
Author(s)
References
See Also
Examples
Description
Make predition for functional response from the CV object obtained by cv.sigcom.
Usage
1
pred.sigcom(fit.obj, X.test, t.y.test=NULL, Z.test = NULL)
Arguments
fit.obj
the CV object obtained by cv.sigcom.
X.test
new observations for the functional predictors. It is a list of length p, the number of functional predcitors. Each element is the observed matrix from a functional predictor, with rows repsenting observation vectors and columns corresponding to the observation time points.
Z.test
new observations for the scalar predictors. It is a matrix with rows representing observation vectors and columns respresenting scalar variables. Default is NULL, indicating no scalar predictors.
t.y.test
a vector of observation time points where values of predicted response curves are to be calculated. If t.y.test=NULL (default), t.y in cv.sigcom will be used.
Value
A matrix containing the predicted response for the new
observations. The number of rows is equal to the sample size of the
new data set, and the number of columns is equal to the length of
t.y.test or t.y when t.y.test=NULL.
Author(s)
Ruiyan Luo and Xin Qi
References
Ruiyan Luo and Xin Qi, (2017) Function-on-Function Linear Regression by Signal Compression, Journal of the American Statistical Association. 112(518), 690-705. http://www.tandfonline.com/doi/abs/10.1080/01621459.2016.1164053
See Also
Examples
1
#See the examples in cv.sigcom().
FRegSigCom documentation built on May 1, 2019, 9:45 p.m.
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Description Usage Arguments Value Author(s) References See Also Examples
Description
Make predition for functional response from the CV object obtained by cv.sigcom.
Usage
1 | pred.sigcom(fit.obj, X.test, t.y.test=NULL, Z.test = NULL)
|
Arguments
fit.obj |
the CV object obtained by |
X.test |
new observations for the functional predictors. It is a list of length p, the number of functional predcitors. Each element is the observed matrix from a functional predictor, with rows repsenting observation vectors and columns corresponding to the observation time points. |
Z.test |
new observations for the scalar predictors. It is a matrix with rows representing observation vectors and columns respresenting scalar variables. Default is NULL, indicating no scalar predictors. |
t.y.test |
a vector of observation time points where values of predicted response curves are to be calculated. If |
Value
A matrix containing the predicted response for the new
observations. The number of rows is equal to the sample size of the
new data set, and the number of columns is equal to the length of
t.y.test or t.y when t.y.test=NULL.
Author(s)
Ruiyan Luo and Xin Qi
References
Ruiyan Luo and Xin Qi, (2017) Function-on-Function Linear Regression by Signal Compression, Journal of the American Statistical Association. 112(518), 690-705. http://www.tandfonline.com/doi/abs/10.1080/01621459.2016.1164053
See Also
Examples
1 | #See the examples in cv.sigcom().
|
R Package Documentation
Browse R Packages
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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