Man pages for linulysses/mcfda
Mean and Covariance Estimation for Functional Data Analysis
| bw.lp1D | select bandwidth for one-dimensional local linear smoother |
| cov.basis | Covariance estimation by basis expansion |
| covfunc | Estimate the cov function from functional data/snippets. |
| cov.pace | PACE approach to covariance estimation |
| cv.partition | the function mimic the cvpartition in MATLAB |
| deriv.fourier | Evaluate derivatives of Fourier basis functions on a grid |
| estimate.delta | estimate the window width of snippets |
| estimate.theta | Estimate the parameters of the correlation structure |
| evaluate.basis | Evaluate orthonormal basis functions on a grid |
| lp1D | one-dimensional local polynomial smoother |
| meanfunc | Estimate the mean function from functional data/snippets |
| plot.meanfunc | plot the estimated mean function |
| predict.covfunc | predict cov functions at new locations |
| predict.meanfunc | predict mean functions at new locations |
| regular.grid | generate a regular grid on a domain |
| rep.col | replicate a column vector into a matrix |
| rep.row | replicate a row vector into a matrix |
| sigma2 | estimate the variance of noise |
| varfunc | Estimate the variance function |
