Description Usage Arguments Value
View source: R/predictSpline.R
A custom spline prediction function, extending linearly with a slope such that prediction never drops below first bisectant
1 2 | predictSpline(fit, newdata, linX, coefsQuad, deriv = 0L, meanVarFit,
minFit, new.knots, degree)
|
fit |
The existing spline fit |
newdata |
points in which the spline needs to be evaluated |
linX |
The x at which the fit becomes linear and intersects the diagonal line |
coefsQuad |
parameters of a quadratic fit |
deriv |
An integer. Which derivative is required? |
meanVarFit |
A character string, indicating which type of mean variance fit is being used |
minFit |
The lower bound of the cubic fit |
new.knots |
The knots at which the spline is to be evaluated |
degree |
The degree of the polynomial fit |
The evaluation of the spline, i.e. the predicted variance
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