- predict.cobs() should have a 'deriv = 0' argument {as predict.smooth.spline()} and deriv in {1,2,3} should work. - cobs() should get an 'keep.data = TRUE' argument as smooth.spline() - For the case 'lambda < 0' (i.e. search over several lambdas), we can become *much* faster in matrix creation, since alle constraint matrices are *not* dependent on lambda at all! - allow constraint = c("increase", "convex") i.e., *BOTH* constraints! - When determining optimal lambda (via 'ic'), allow a "+ 1 S.E. - rule" instead of simply taking the arg_min - dito for knot selection - Documentation (and examples!) for the intermediate/ auxiliary functions qsbks() and drqssbcs(), i.e. man/qbsks.Rd & man/drqssbc.Rd - need examples with degree = 1 and several other values of tau also extreme cases of interpolation and global linear/quadratic - want to have examples of all constraints, including "periodic" and even more 'pointwise' ! - src/splines.c is UN-needed in R --- rather use library(splines) !! ------------- now have .Call(*) there instead of .C() here. partly done: now use .splBasis() and .splValue() <<<<-- R/splines.R --> --> tests/spline-ex.R shows how .splBasis() can be done via library(splines) - lambda < 0; for each pp.lambda, instead of (only) $sic, return both components : Log.lik. and p[lambda] ( = k[lambda] ), the dim. ----------------------------- Old `TODOs' which are done (here for reference only): ========== ==== - add the three interesting real data examples from the COBS "paper". in the paper, they say that S-plus code for these examples is available as well. --> see also ./inst/scripts/ and ./tests/ - example(cobs) gives lots of warnings; the upper and lower quantiles are not plotted (not properly computed ??) - man/cobs.Rd needs the current reference list ! - cobs() should keep its call and return an object of class "cobs". Then print.cobs(), summary.cobs(), predict.cobs() and plot.cobs() should be designed! ---> this is now done { --> old & original code in ./R/cobsOld.R }