SplineEst {CollocInfer} | R Documentation |
Spline Estimation Functions
Description
Model-based smoothing; estimation, objective criterion and derivatives.
Usage
SplineEst.NewtRaph(coefs,times,data,lik,proc,pars,
control=list(reltol=1e-12,maxit=1000,maxtry=10,trace=0))
SplineCoefsList(coefs,times,data,lik,proc,pars,sgn=1)
SplineCoefsErr(coefs,times,data,lik,proc,pars,sgn=1)
SplineCoefsDC(coefs,times,data,lik,proc,pars,sgn=1)
SplineCoefsDP(coefs,times,data,lik,proc,pars,sgn=1)
SplineCoefsDC2(coefs,times,data,lik,proc,pars,sgn=1)
SplineCoefsDCDP(coefs,times,data,lik,proc,pars,sgn=1)
Arguments
coefs |
Vector giving the current estimate of the coefficients in the spline. |
times |
Vector observation times for the data. |
data |
Matrix of observed data values. |
lik |
|
proc |
|
pars |
Parameters to be used for the processes. |
sgn |
Is the minimizing (1) or maximizing (0)? |
control |
A list giving control parameters for Newton-Raphson optimization. It should contain
|
Details
SplineEst.NewtRaph
performs a simple Newton-Raphson estimate for the optimal value of the coefficients.
This estimate lacks the convergence checks of other estimation packages, but may yeild a fast solution when needed.
Value
SplineEst.NewtRaph |
Returns a list that is the result of the optimization with elements
|
SplineCoefsList |
Collates the gradient calculations and returns a list with elements
|
SplineCoefsErr |
The complete data log likelihood for the smooth; the inner optimization objective. |
SplineCoefsDC |
The derivative of |
SplineCoefsDP |
The derivative of |
SplineCoefsDC2 |
The second derivative of |
SplineCoefsDCDP |
The second derivative of |
The output of gradients is in terms of an array with dimensions corresponding to derivatives. Derivatives with with respect to coefficients are given in dimensions before those that give derivatives with respect to parameters.