A wrapper function to call functions in the fda package to obtain smoothed estimated derivatives at a specified order
A wrapper function to call functions in the fda package to obtain smoothed estimated derivatives at a specified order
getdx(theTimes, norder, roughPenaltyMax, lambda, dataMatrix, derivOrder)
theTimes |
The time points at which derivative estimation are requested |
norder |
Order of Bsplines - usually 2 higher than roughPenaltyMax |
roughPenaltyMax |
Penalization order. Usually set to 2 higher than the highest-order derivatives desired |
lambda |
A positive smoothing parameter: larger –> more smoothing |
dataMatrix |
Data of size total number of time points x total number of subjects |
derivOrder |
The order of the desired derivative estimates |
A list containing: 1. out (a matrix containing the derivative estimates at the specified order that matches the dimension of dataMatrix); 2. basisCoef (estimated basis coefficients); 3. basis2 (basis functions)
Chow, S-M. (2019). Practical Tools and Guidelines for Exploring and Fitting Linear and Nonlinear Dynamical Systems Models. Multivariate Behavioral Research. https://www.nihms.nih.gov/pmc/articlerender.fcgi?artid=1520409
Chow, S-M., *Bendezu, J. J., Cole, P. M., & Ram, N. (2016). A Comparison of Two- Stage Approaches for Fitting Nonlinear Ordinary Differential Equation (ODE) Models with Mixed Effects. Multivariate Behavioral Research, 51, 154-184. Doi: 10.1080/00273171.2015.1123138.
#x = getdx(theTimes,norder,roughPenaltyMax,sp,out2,0)[[1]] #Smoothed level #dx = getdx(theTimes,norder,roughPenaltyMax,sp,out2,1)[[1]] #Smoothed 1st derivs #d2x = getdx(theTimes,norder,roughPenaltyMax,sp,out2,2)[[1]] #Smoothed 2nd derivs
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