Changes from Version 0.15-36 to 0.15-37 [31-Dec-2022] * Fixed issue in snomadr.cpp reported by Brian Ripley "warning: 'sprintf' is deprecated: This function is provided for compatibility reasons only. Due to security concerns inherent in the design of sprintf(3), it is highly recommended that you use snprintf(3) instead. [-Wdeprecated-declarations]" (thanks Zhenghua!) * Fixed issue reported - compilation error on Alpine Linux #9 Changes from Version 0.15-35 to 0.15-36 [18-Oct-2022] * Fixed warning: a function definition without a prototype is deprecated in all versions of C and is not supported in C2x [-Wdeprecated-non-prototype] (thanks Zhenghua!) Changes from Version 0.15-34 to 0.15-35 [09-Oct-2022] * Explicit acknowledgment in DESCRIPTION of code gsl_bspline.c/.h adapted from the GNU GSL library with further details appended to gsl_bspline.c/.h (thanks to Professor Brian Ripley for noting this oversight). Changes from Version 0.15-33 to 0.15-34 [30-Mar-2022] * Fixed warnings flagged on CRAN (thanks Zhenghua!) [i) snomadr.cpp:374:60: warning: void operator delete(void*, std::size_t) called on pointer returned from a mismatched allocation function [-Wmismatched-new-delete], ii) nomad_src/Sgtelib_Model_Search.cpp:957:43: warning: array subscript -1 is outside array bounds of bool [2147483647] [-Warray-bounds]] * Additional casting of x as as.matrix() in is.fullrank() Changes from Version 0.15-32 to 0.15-33 [02-Feb-2021] * Updated NOMAD to version 3.9.1 * Removed dependency on C++11 random_shuffle per recommendation from R development team (thanks Zhenghua!) * Followed R core team request to "Please move rgl to Suggests and use conditionally (see 1.1.3.1 of Writing R Extensions) at the next package update" Changes from Version 0.15-31 to 0.15-32 [19-Nov-2019] * Corrected return value for mgcv_tmm() (was void, not valid address of R object) * Added crs.messages=FALSE capabilities to clsd() Changes from Version 0.15-30 to 0.15-31 [01-May-2018] * basis="auto" was default, doc/code discrepancy fixed * Hattip to Thibault Vatter who patched an issue with weights not being functional in crsiv.R * Fixed issue with compiler compliance to support ICC and retain backwards compatability with MSVC C++ Changes from Version 0.15-29 to 0.15-30 [03-Dec-2017] * dim.plot() replaced by n2mfrow() for determining layout of multiple figures on one device * Fixed issue where, occasionally during cross-validation, execution of the function npglpreg() could halt with an error indicating missing value needed where TRUE/FALSE needed Changes from Version 0.15-28 to 0.15-29 [06-Oct-2017] * Fixed issue pointed out by Brian Ripley (thanks!) about double ** _X; in the nomad code * Updated licence to GPL (>= 3) Changes from Version 0.15-27 to 0.15-28 [06-Oct-2017] * Zhenghua worked his magic to furnish a computationally efficient glp.model.matrix using a C backend similar to Simon Wood's C backend for his tensor.product.model.matrix * Fixed issue with integer predictors and NOMAD for npglpreg() arising from upgrade to latest version of NOMAD * Fixed issue with min.poll.size arising from upgrade to latest version of NOMAD Changes from Version 0.15-26 to 0.15-27 [06-May-2017] * Zhenghua fixed minor issue with dim.bs() * Incorporating Simon Wood's C-based tensor product code (was using his R-based code, the C code is substantially faster) * Naming of variables in NOMAD port aligned with Brian Ripley's comment ('Identifiers starting with an underscore followed by an upper-case letter or another underscore are reserved for system macros and should not be used in portable code (including not as guards in C/C++ headers).') Changes from Version 0.15-25 to 0.15-26 [29-April-2017] * Zhenghua patched up issues arising with windows build * crs_init.c attempts to deal with registration issue/note Changes from Version 0.15-24 to 0.15-25 [29-April-2017] * Fixed glitch that could potentially arise when computing derivatives and multiple predictors are assigned degree 0 when using the glp basis * Updated NOMAD to latest version (3.8, released March 2017) Changes from Version 0.15-23 to 0.15-24 [18-Dec-2014] * Move option init from .onAttach to .onLoad in zzz.R (Bernd Bischl) * Reworded DESCRIPTION (request from Kurt Hornik) Changes from Version 0.15-22 to 0.15-23 [11-Aug-2014] * Fixed bugs on setting seed in snomadr so that successive calls with restarting result in the same solution (thanks to Arne Henningson for detecting and reporting this issue) * Addressed issue with cv.aic and npglpreg where degenerate solution could occur when shrinking was invoked * Enhanced the robust measure of scale to include mad which is more robust than IQR Changes from Version 0.15-21 to 0.15-22 [22-Jan-2014] * crs.messages=FALSE was being ignored in frscv, krscv, frscvNOMAD, and krscvNOMAD, as was the passing of additional arguments via opts=list() to snomadr from certain functions * Default settings for tuning parameters for snomadr in npglpreg have been optimized based on extensive simulations for simulated and real datasets (we `optimized the optimizer' so to speak) * Fixed glitch in npglpreg where cv.aic was only working properly for the local constant estimator (i.e. degree=0) * bwscaling is deprecated in the latest (development) version of np which necessitated changes to npglpreg. In the process the way scaling is performed ought to be more robust in general due to changes to default starting values for numeric predictors Changes from Version 0.15-19 to 0.15-21 [08-Jan-2014] * Addressed issues with certain non-package files being included via use of .Rbuildignore * NOMAD team corrected dereferencing null pointer in Mads.cpp that was uncovered through the use of UB sanitizer checks with clang Changes from Version 0.15-18 to 0.15-19 [30-Dec-2013] * Updated snomadr to NOMAD 3.6.2 (released Dec 2013) which resolves crash/incompatibility with the clang compiler on Mac OS X Mavericks 10.9.1 * Added new function clsd() that does logspline regression jointly choosing the degree and number of segments (knots) - this is to be treated as beta but the univariate continuous only case currently implemented is capable of outperforming existing logspline methods that set the spline degree to an ad hoc value (3) * npglpreg() now optimizes at the level of the bandwidth scaling factors (thanks to Sebastien Le Digabel for the suggestion) to bring parameters to a `common scale' * For cross-validation with npglpreg() we test for very large bandwidths for the continuous predictors (> bandwidth.switch robust standard deviations) then switch to the global polynomial approximation for computation speed (produces identical results but uses global least squares rather than local least squares). This can result in substantial improvements when large bandwidths are appropriate. Combined with trees (in progress in np) this could lead to marked reductions in computation time with zero loss in accuracy Changes from Version 0.15-17 to 0.15-18 [29-Dec-2012] * Using .onUnload rather than .Last.lib in zzz.R * Added options to smooth residuals for stopping rule in crsiv (i.e. smooth y-phi(z)~w as opposed to separately smoothing y~w and phi(z)~w) * Added options to input starting values for crsiv and crsivderiv * Stopping rules for crsiv and crsivderiv modified Changes from Version 0.15-16 to 0.15-17 [04-Jun-2012] * Updated NOMAD from 3.5.0 (released Jan 2011) to 3.5.1 (released Mar 2012) Changes from Version 0.15-15 to 0.15-16 [30-Apr-2012] * Fixed bug when deriv= is used in crs() (derivatives for categorical variables were not correct in some cases - derivatives computed by plot and plot-data were correct however) * Fixed issue when plot called with "plot-data" or "data" and par(mfrow()) is not reset * Startup message points to the faq, faq is now a vignette * Glitch fixed in npglpreg() where kernel types were not being passed to the NOMAD solver... * Added ckerorder option to npglpreg() * More information output by summary for npglpreg() objects (kernel type, order etc.) * tol for determining ill-conditioned bases now consistent with Octave/Matlab etc. and uses the tolerance max(dim(x))*max(sqrt(abs(e)))*.Machine$double.eps Changes from Version 0.15-14 to 0.15-15 [16-Apr-2012] * NOTE: ** major change in default setting ** Default basis set to "auto" from "additive" for more robust results when using default settings with more than one continuous predictor (at the cost of additional computation for all supported bases, more memory required). Warnings changed to reflect this, additional warnings provided, but mainly when cv="none" (i.e. user is doing things manually and failing to provide defaults) * Added switch for discarding singular bases during cross-validation (singular.ok=FALSE is default, so default is to discard singular bases) * More stringent checking for ill-conditioned bases during cross-validation - previous checks were insufficient allowing poorly conditioned bases to creep into the final model (this may result in increased runtime for large datasets and multivariate tensor models) * Potential runtime improvement for large bases (test for ill-conditioned bases was still relying in parts on rcond(t(B)%*%B), now using crossprod(B) which is more computationally efficient than rcond(t(B)%*%B) and has a substantially smaller memory footprint) * No longer report basis type for one continuous predictor as all bases are identical in this case Changes from Version 0.15-13 to 0.15-14 [22-Mar-2012] * Added support for weights to crs() * Corrected issue with reporting of cv function value by summary() with quantile regression splines * Test for coexistence of pruning and quantile regression splines and stop with a message that these cannot coexist * Check for valid derivative integer Changes from Version 0.15-12 to 0.15-13 [05-Mar-2012] * Added new function crsivderiv() * More options added to crsiv() * Modified vignette (spline_primer) * Corrected error in demo for IV regression when exhaustive search was selected (nmulti needed to be set though it is not used) * Changes to code to improve compliance with R `Writing portable packages' guidelines and correct partial argument matches Changes from Version 0.15-11 to 0.15-12 [7-Dec-2011] * Added option to limit the minimum degrees of freedom when conducting cross validation (see cv.df.min which defaults to 1) which can save memory and computation time for large sample sizes by avoiding computation of potentially very large dimensioned spline bases Changes from Version 0.15-10 to 0.15-11 [3-Dec-2011] * Fixed glitch in bwtype="auto" when adaptive_nn is selected Changes from Version 0.15-9 to 0.15-10 [3-Dec-2011] * Fixed regression in code when using cv.func=cv.aic * Added option bwtype="auto" for npglpreg (automatically determine the bandwidth type via cross-validation) Changes from Version 0.15-8 to 0.15-9 [25-Nov-2011] * Fixed glitch when computing derivatives with crs and multiple predictors are of degree zero * Added support for parallel npglpreg (calls npRmpi rather than np - see demo) * Improved handling of complex bases via dim.bs (test for negative degrees of freedom prior to attempting to construct the basis function - dramatically reduces memory overhead and can cut down on unnecessary computation) Changes from Version 0.15-7 to 0.15-8 [16-Nov-2011] * Added support for is.fullrank testing for generalized local polynomial kernel regression for cross-validation (default remains ridging a la Seifert & Gasser), replaced rcond(t(X)%*%X) with is.fullrank(X) (smaller memory footprint for large datasets) * Fixed glitch with derivative computation when one or more degrees is 0 when kernel=TRUE and additionally when one or more factors is excluded when using kernel=FALSE * Fixed issue with reported cross-validation score only corresponding to leave-one-out cross-validation by passing back cv function from solver rather than computing post estimation * Added ability to estimate quantile regression splines * More rigorous testing for rank deficient fit via rcond() in cv function * Fixed issue where degree.min was set > 1 but initial degree was 1 (corresponding to the linear model which is the default for the initial degree otherwise) * Added the option to treat the continuous bandwidths as discrete with lambda.discrete.num+1 values in the range [0,1] which can be more computationally efficient when a `quick and dirty' solution is sufficient rather than conducting mixed integer search treating the lambda as real-valued * Corrected incorrect warning about using basis="auto" when there was only one continuous predictor Changes from Version 0.15-6 to 0.15-7 [24-Oct-2011] * Added logical model.return to crs (default model.return=FALSE) which previously returned a list of models corresponding to each unique combination of the categorical predictors when kernel=TRUE (the memory footprint could be potentially very large so this allows the user to generate this list if so needed) Changes from Version 0.15-5 to 0.15-6 [17-Oct-2011] * Compiler error thrown on some systems due to changes in Eval_Point.hpp corrected Changes from Version 0.15-4 to 0.15-5 [16-Oct-2011] * Thanks to Professor Brian Ripley, additional Solaris C/C++ compiler warnings/issues have been resolved * Some internal changes for soon to be deprecated functionality (sd() expected to be deprecated shortly) Changes from Version 0.15-3 to 0.15-4 [15-Oct-2011] * Extended the gsl.bs functionality to permit out-of-sample prediction of the spline basis and its derivatives * Added option knots="auto" to automatically determine via cross-validation whether to use quantile or uniform knots * Minor changes to help page examples and descriptions and to the crs vignette Changes from Version 0.15-2 to 0.15-3 [05-Sep-2011] * Fixed glitch when all degrees are zero when computing the cross-validation function (also fixes glitch when all degrees are zero when plotting the partial surfaces) * Added new function crssigtest (to be considered in beta status until further notice) * Added F test for no effect (joint test of significance) in crs summary * Both degree and segments now set to one for first multistart in crs (previously only degree was, but intent was always to begin from a linear model (with interactions where appropriate) so this glitch is corrected) * Test for pathological case in npglpreg when initializing bandwidths where IQR is zero but sd > 0 (for setting robust sd) which occurs when there exist many repeated values for a continuous predictor * Added `typical usage' preformatted illustrations for docs Changes from Version 0.15-1 to 0.15-2 [30-Jul-2011] * Renamed COPYING file to COPYRIGHTS Changes from Version 0.15-0 to 0.15-1 [29-Jul-2011] * Automated detection of ordered/unordered factors implemented * Initial degree values set to 1 when conducting NOMAD search (only for initial, when nmulti > 1 random valid values are generated) * Multiple tests for well-conditioned B-spline bases, dynamic modification of search boundaries when ill-conditioned bases are detected, and detection of non-positive degrees of freedom and full column rank of the spline basis (otherwise the penalty sqrt(.Machine$double.xmax) is returned during search) - this can lead to a significant reduction in the memory footprint * Added support for generalized B-spline kernel bases (varying order generalized polynomial) * Corrected issue with plot when variables were cast as factors in the model formula * Fixed glitch with return object and i/o when cv="bandwidth" and degree=c(0,0,...,0) * Added tests for pathological cases (e.g. optimize degree and knots but set max degree to min degree or max segments to min hence no search possible). * Added argument cv.threshold that uses exhaustive search for simple cases where the number of objective function evaluations is less than cv.threshold (currently set to 1000 but user can set). Naturally exhaustive search is always preferred but often unfeasible, so when it is feasible use it. * Added additional demos for constrained estimation (Du, Parmeter, and Racine (2011)), inference, and a sine-based function. * Substantial reductions in run-time realized. - Product kernel computation modified for improved run-time of kernel-based cross-validation and estimation. - Moved from lsfit to lm.fit and from lm to lm.wfit/lm.fit in cv.kernel.spline and cv.factor.spline (compute objective function values). Two effects - R devel indicates lm.fit/lm.wfit are more robust (confirmed for large number of predictors) and much faster cv.kernel.spline function emerges (run-time cut 20-30%). - The combined effects of these changes are noticeable. For instance, run-time for wage1 with 7 predictor cross-validation goes from 510 seconds in 0.15-0 to 304 seconds due to use of lm.fit/lm.wfit described below to 148 seconds due to the modified kernel function. Changes from Version 0.14-9 to 0.15-0 [23-Jun-2011] * Thanks to Professor Brian Ripley, compile on Solaris system issues are resolved, and check/examples are reduced in run time to alleviate the excessive check times by the R development team. Many thanks to them for their patience and guidance. * Minor changes to radial_rgl demo Changes from Version 0.14-8 to 0.14-9 [20-Jun-2011] * Cleaned up issues for creating binary for windows * Setting seed in crs -> frscvNOMAD/krscvNOMAD fed to snomadr.cpp via snomadr.R for starting points when nmulti > 0 * frscvNOMAD and krscvNOMAD will check the number of times the objective function, compare with MAX_BB_EVAL and give the warning if the maximum is reached (nmulti * MAX_BB_EVAL - note this will only detect the case where every restart hit MAX_BB_EVAL) * Increased default MAX_BB_EVAL from 500 to 10000 (makes a difference for difficult problems) and modified default EPSILON in NOMAD along with other parameters (MIN_MESH_SIZE, MIN_POLL_SIZE) to reflect actual machine precision (using R's .Machine$double.eps where NOMAD fixed EPSILON at 1e-13) * Zhenghua added help functionality for retrieving help via snomadr * Now default number of restarts in crs is 5 (zero is not reliable and I want sensible defaults in this package - higher is better but for many problems this ought to suffice) * Corrected glitches in interactive demos where options were not being passed, updated docs to reflect demos Changes from Version 0.14-7 to 0.14-8 [10-Jun-2011] * crsiv now returns a crs model object that supports residuals, fitted, predict and other generic functions. Note that this approach is based on first computing the model via regularization and then feeding a transformed response to a crs model object. You can test how close the two approaches are to one another by comparing model$phihat with fitted(model) via all.equal(as.numeric(fitted(model)),as.numeric(model$phihat)) Changes from Version 0.14-6 to 0.14-7 [09-Jun-2011] * Checking for non-auto basis corrected, modify crsiv to use auto basis. * When degree==0 segments is not used, so set segments==1 in this case (could be NA). Changes from Version 0.14-3 to 0.14-6 [08-Jun-2011] * Initial release of the crs package on CRAN. * Added internal support for NOMAD via snomadr (Zhenghua's simple NOMAD interface). Ideally in the future Sebastien Le Digabel will be releasing an R package for NOMAD and we will be able to dump our internal code and rely on his R package. In the meantime this allows us to proceed with an R package. * Numerous internal changes incorporated, most noteworthy additional flexibility in search provided by degree.min, degree.max, segments.min, and segments.max. Replaces basis.maxdim. * Default now search via NOMAD, kernel=TRUE. * crsiv implemented. * Engel95 data added. * Demos added. Changes from Version 0.14-2 to 0.14-3 [01-May-2011] * Zhenghua migrated the necessary files from the gsl so that the crs package is now standalone with the exception of NOMAD. Changes from Version 0.14-0 to 0.14-2 [30-Apr-2011] * Zhenghua migrated the bare-bones code required for the mgcv functions uniquecombs and tensor.prod.model.matrix, and I migrated the associated manpages, modified NAMESPACE and now the package does not require loading of mgcv which was sub-optimal. * dropped cv.norm and replaced with cv.func=c("cv.ls","cv.gcv","cv.aic"). Changes from Version 0.13-8 to 0.14-0 [14-Apr-2011] * tensor products now working properly (need gsl.bs intercept and no intercept in lm()) so dumped "additive-tensor" option and had to rework code to support additive (lm() has intercept, gsl.bs no intercept here) etc. In the process realized derivatives were all effed up and now for the first time they work (with segments being any value at all etc.). Changes from Version 0.13-7 to 0.13-8 [30-Jan-2011] * cv now default, increased basis.maxdim to 10 * segments and degree hit different maxima (basis.maxdim+1, basis.maxdim) but `degree equal to basis.maxdim' warning was only being issued when equal to basis.maxdim. * restarts was not being passed to krscv Changes from Version 0.13-6 to 0.13-7 [9-Dec-2010] * added option to choose both degree and knots independently for each predictor and (more importantly) cross-validate both Changes from Version 0.13-5 to 0.13-6 [8-Dec-2010] * added option to use either uniform knots (equally spaced segments) or quantile knots (equal number of observations in each segment) Changes from Version 0.13-4 to 0.13-5 [17-Apr-2010] * changed package and function names to `crs' as Lijian strictly prefers `regression spline' to `smoothing spline' (The major difference is to place knots on sample points (smoothing spline, Wahba) or on equidistant deterministic points (B spline, Stone)) Changes from Version 0.13-3 to 0.13-4 [07-Apr-2010] * fixed annoying "Working... Working" in plot (message produced by predict.*.spline sufficient here) * added option for L1 CV (incomplete as properly this would require L1 estimation as well) * neglected to set cv and cv.pruned when degree is zero (fixed) * adjusted R-squared corrected Changes from Version 0.13-2 to 0.13-3 [28-Mar-2010] * had to revamp derivative code to support pruning by taking out the reordering prior to derivative estimation - new approach is more natural with less issues. Examples all pass with flying colors * had to modify the add1.lm function (modified version is add1.lm.cv) to flesh out stepCV Changes from Version 0.13-1 to 0.13-2 [28-Mar-2010] * modified stepAIC code from the MASS package to admit the cross-validation objective function, renamed to stepCV to not clobber users using stepAIC - this is a three line addition of the extractCV() function followed by wholesale replacement of AIC with CV - appears to work perfectly and now pruning returns models that indeed improve in terms of CV (was mixing objective functions pruning with stepAIC at the final stage (BIC) and hence testing for model that improves etc.) Changes from Version 0.13-0 to 0.13-1 [25-Mar-2010] * migrated pruning inside predict.factor.spline, derivatives not crashing and are working for one continuous regressor - one major benefit is that the object is now a proper cssreg object hence predict etc. are fully supported (the old function prune.cssreg could not do this) Changes from Version 0.12-6 to 0.13-0 [22-Mar-2010] * added prune.cssreg that allows for a final pruning stage a la Friedman's MARS, or alternatively a BIC model selection criterion to complement cross-validation - I prefer first running cross-validation as it operates at the _variable_ level while stepAIC operates at the individual basis level * added passing back of hatvalues from predict.factor.spline and predict.kernel.spline to facilitate default plot (added Cook's Distance) * fixed corner case via data.frame(as.matrix(P)) * added passing of se back in fitted.values[,4] so now confidence intervals for differences in levels are implemented (though no cov() term). Also, went through code and cleaned up all lingering issues. A true milestone hence the new cssver Changes from Version 0.12-5 to 0.12-6 [22-Mar-2010] * lwr/upr error bounds (95% cis) now being returned and used in plot when ci=TRUE - lingering issue with differences in levels Changes from Version 0.12-4 to 0.12-5 [21-Mar-2010] * no longer using ncoeffs as a passable parameter, rather nbreak (>=2) * all appears to be working smoothly. Now passing back model/model list for cssreg. Next standard errors from predict and for derivatives. Changes from Version 0.12-3 to 0.12-4 [20-Mar-2010] * kernel derivatives implemented and appear to be working properly. drop=FALSE populated so that as.matrix() no longer needed and handles corner cases of nrow=1 in matrices etc. This is the first real fully functioning version with multivariate derivatives etc. appearing to work. Passes R CMD check and numerous toy examples. One big improvement is adding factor.to.numeric to splitFrame() to admit both numeric and character string factors. Changes from Version 0.12-2 to 0.12-3 [20-Mar-2010] * streamlining code, removing now redundant functions (prod.spline can be handled by prod.kernel.spline so removed former and renamed the latter to prod.spline throughout) Changes from Version 0.12-1 to 0.12-2 [16-Mar-2010] * fitted and predict are faster than the matrix multiplication I am using (not to mention simpler) - moving to these for simplicity and to facilitate standard errors Changes from Version 0.12-0 to 0.12-1 [16-Mar-2010] * multivariate gradients working with tensor enabled/disabled - now cleaning up to match np in terms of functionality Changes from Version 0.11-9 to 0.12-0 [13-Mar-2010] * gradients successfully implemented - remains to get factor/ordered in plot and allowing for plot to handle factor in formula (not a high priority) Changes from Version 0.11-8 to 0.11-9 [13-Mar-2010] * adding S3 plot class * support for mean and (continuous) derivatives with drawback that data must be cast as a factor to work Changes from Version 0.11-6 to 0.11-8 [13-Mar-2010] * multivariate bugs squashed for factor estimator... now to test for kernel... if working, we move on to a plot method for the fit and derivatives Changes from Version 0.11-5 to 0.11-6 [11-Mar-2010] * multivariate derivatives implemented and appear to be working, at least when tensor is disabled so I can verify * next to add to predict in order to get evaluation (attribute? could add gradients function to do this? a bit odd but not sure what else would be easier) Changes from Version 0.11-4 to 0.11-5 [11-Mar-2010] * about to begin adding derivatives Changes from Version 0.10-8 to 0.11-4 [11-Mar-2010] * total reworking of package for S3 methods - now one function cssreg that does it all, supports predict properly etc. Big effort but now much happier with code (streamlined and simpler to maintain) * gsl spline support for derivatives, have dumped spline package as it is missing its S-Plus counterpart's derivative capabilities Changes from Version 0.10-8 to 0.10-9 [4-Mar-2010] * cleaned up and lingering bugs gone related to use of predict.bs (now compares exactly with pre package code) Changes from Version 0.10-7 to 0.10-8 [4-Mar-2010] * added factor smoothing splines using indicator basis functions * this (fssreg) supplants ssreg, so will have a change from x=matrix to x=data frame shortly * corrected glitch in B-splines and reverting to using predict.bs as previously * removing poly() splines and switch Changes from Version 0.10-6 to 0.10-7 [2-Mar-2010] * removed straight search pending MIQP solver in R * added better i/o to help gauge time to completion * fixed bug in dimension warning * added more trapping of issues for small cells having less data than the spline degree etc. prior to beginning search Changes from Version 0.10-5 to 0.10-6 [1-Mar-2010] * multivariate x now implemented and working in ssregcv and cssregcv for exhaustive search - issues remain with straight search (parscale, ndeps etc.) Changes from Version 0.10-4 to 0.10-5 [27-Feb-2010] * new functions predict.spline, model.spline, and cv.spline automatically handle K=0 and z/no z cases - code much more modular hence handling multivariate x will in principle be simplified Changes from Version 0.10-3 to 0.10-4 [27-Feb-2010] * implementing tensor product splines in function to facilitate multivariate x and make code base easier to handle - handle base case of zero in this function so use intercept=TRUE * revisiting search with discrete K Changes from Version 0.10-2 to 0.10-3 [26-Feb-2010] * added S3 predict method for ssreg and cssreg * added ssreg and ssregcv for continuous-only x case to facilitate comparison of improvements * added wage1 and cps71 data and examples Changes from Version 0.00-0 to 0.10-2 [24-Feb-2010] * S3 methods for summary, print * created functions cssreg and cssregcv * initial version of the css package