CVspline: Leave one-subject out Cross-validation score for spline fit
In npmldabook/npmlda: Non-Parametric Models for Longitudinal Data Analysis
Description
Usage
Arguments
References
Description
Leave one-subject out Cross-validation score for spline fit
Usage
1
CVspline(Xvec, Yvec, ID, nKnots, Degree, Wt)
Arguments
Xvec, Yvec
numeric vectors of data values, Xvec and Yvec must have the same length.
ID
subject ID of the data value
nKnots
number of equally-spaced knots
Degree
degree of polynomial splines
Wt
a weight vector. For longitudinal data, Wt=1/N corresponds to measurement uniform weight and Wt=1/(nni) corresponds subject uniform weight.
References
Wu, C.O. and Tian, X. Nonparametric Models for Longitudinal Data: With Implementation in R. Chapman & Hall/CRC.
2018.
npmldabook/npmlda documentation built on May 25, 2019, 10:41 p.m.
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Description Usage Arguments References
Description
Leave one-subject out Cross-validation score for spline fit
Usage
1 | CVspline(Xvec, Yvec, ID, nKnots, Degree, Wt)
|
Arguments
Xvec, Yvec |
numeric vectors of data values, Xvec and Yvec must have the same length. |
ID |
subject ID of the data value |
nKnots |
number of equally-spaced knots |
Degree |
degree of polynomial splines |
Wt |
a weight vector. For longitudinal data, Wt=1/N corresponds to measurement uniform weight and Wt=1/(nni) corresponds subject uniform weight. |
References
Wu, C.O. and Tian, X. Nonparametric Models for Longitudinal Data: With Implementation in R. Chapman & Hall/CRC. 2018.
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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