Provides tools for working with nonlinear least squares problems. It is intended to eventually supersede the 'nls()' function in the R distribution. For example, 'nls()' specifically does NOT deal with small or zero residual problems as its Gauss-Newton method frequently stops with 'singular gradient' messages. 'nlsr' is based on the now-deprecated package 'nlmrt', and has refactored functions and R-language symbolic derivative features.
TODO: o Should we use model.frame() anywhere?
o Need to ensure masks consistent between nlfb and nlxb.
o Need to check if all parameters masked.
o Should allow jacfn to be specified in quotation marks to
call numerical approximations of different types, as per
optimr / optimx.
o Vignette to explain how stabilized Marquardt works, since
Compact Numerical Methods book is hard to find.
180128 o A minor fix to derivs.R to avoid a bug when multiple partials are computed at once
o isFALSE now becoming part of R, so nlsr::isFALSE has been
adjusted to be that code
171004 o Minor edits to note nlmrt (deprecated) origins, and remove vignette dependency on that package
170618 o Minor repairs to vignette examples with other packages
170320 o Added Vignette Title fields to the three vignettes
170117 o rename modeldoc to rjfundoc. It is not simple to add documentation to ssgrfun objects.
170116 o summary no longer invisible?
o summary for nlxb and nlfb both now should work.
If there is no name for a parameter, the name p_(position)
is created.
o weights should be working OK. Residuals will be weighted ones.
o added resid.nlsr() function. However, predict.nlsr() is NOT
present, since we can create problems with residuals (e.g.,
nonlinear equations) that do not have a model structure
170113 o output of summary.nlsr is class = "summary.nlsr" like summary.nls is "summary.nls"?
170110 o weights (fixed) added and documented in nlsr-devdoc.Rmd o nlfb: sumsquares via crossprod needs to be as.numeric(). Done.
170108 o removed dot args from nlxb declaration and its internal call to nlfb(), and fixed nlxb.Rd. Note nls() help says of dot args "None are used at present."
o moved model2rjfunx and .Rd file to inst/dev-files
o Note that nlfb() can use functionally created weights,
but nls uses FIXED weights. We have added fixed weights to
nlxb() and pass them to nlfb() via its dot args.
170107 o expanded dex() examples to show object class of result. Note that "language" class encompasses "expression".
o made clear where the .MissingVal usage is to be found in
Rd file for nlsDeriv.
o in nlsr-devdoc.Rmd added silly joe(x) example to show
possible trouble spot
170102 o Cleanup of package New function dex() to prepare input for nlsDeriv() Renamed Deriv to nlsDeriv. New names codeDeriv and fnDeriv.
161222 o newDeriv() now issues a warning if a derivative definition is changed.
161019 o Changed names nlsrxb and nlsrfb to nlxb and nlfb and removed superfluous nlfb.
161018 o Problem with vignettes (why?). optimx is needed (why?)
161007 o Sort out nlsrxb to use Deriv vs deriv (vs Deriv from French) ??
o Note the ?? in all the codes. Simplify!
o More detailed build of rjfun to use approximations when derivs
not available.
o Simple GN code needed to show what happens -- should be able
to write a VERY simple one for the vignette. Possibly
not include in the code of nlsr.
o Origin of NaN's in bounded examples. Can they be avoided?
Handling of NaN in Jacfun ?? Need an example.
o Does it make sense to have unconstrained version of nlfb
when there are no masks or bounds?
o Rename modss, modgr to res2ss, res2gr
o Option for numerical Jacobian -- control numJac = TRUE?, with
routine in nlmrt.R ?? elsewhere.
Way of using a "gradient" attribute when the model formula is
specified like
y ~ SpecialFn(xx, zz)
which would allow functions not differentiable by deriv()
o Weighted least squares example, especially in nlxb.
o Issue when npar = 1 -- does it work?
o check and fix examples? Partly done 140719 tests?
o check impact of use of Deriv vs deriv and document!
o make sure change to rjfun using "gradient" is clean in nlsrxb
o partially linear nls models. How to incorporate? Note Rust and Oleary.
o nlsr when it exceeds fn or jac count, returns bad solutions
that won't print.
Changes in nlsr version 2016-10.3 o name change to nlsr and consequent changes o minor fixes
Changes in nlsr version 2014-7.28
Changes in nlsr version 2014-7.27 o Deriv() etc. o model2rjfun() etc. o changes to nlsrxb structure
Changes in nlsr version 2014-7.19 o The parameters MUST be named when setting up model2resfun etc., but the resulting function can be called with an un-named vector of parameters. o Name reset to reflect intent to substitute for nls() o wrapnls replaced by wrapnlsr o use of ... args replaced with data = mydata (dataframe) o 1-sided models which start with the tilde are now allowed in nlsr functions.
Changes in nlmrt version 2013-8.26 o Relative offset convergence test (not exactly as in nls()) residual and jacobian in summary & print methods o coef() method in nlmrt.R so names carried through o summary() and print() cleanup o partial and minor documentation improvement
Changes in nlmrt version 2013-8.10 o fix line length issue in examples
Changes in nlmrt version 2013-7.9 o Added control list elements to .Rd files for nlxb and nlfb, with reference in wrapnls. o Put in a test for very small sum of squares in nlfb and nlxb.
Changes in nlmrt version 2013-3.16 o Result element coeffs changed to coefficients. This alters wrapnls.R code also.
Changes in nlmrt version 2012-9.03
o More features in summary().
Changes in nlmrt version 2012-9.03
o summary() for output from different functions. Should display constraints if possible as per JNMWS codes. Warnings / Notes fixed re: dependencies in vignette, methods.
o Sort out display in vignette Note warning "unstated dependencies in vignette"
Changes in nlmrt version 2012-8.12
o Bounds and masks examples in nlmrt-vignette.
Changes in nlmrt version 2012-8.04 o Vignette nlmrt-vignette updated.
o Functions to convert expression to residual, Jacobian, sum of squares and gradient functions (for use with optimx or nlmrt:nlfb or minpack.lm:nls.lm
o The examples in ./inst/examples/ are calling routines that have been renamed. These have, I believe, been fixed.
o nlfb() needs an explicit Jacobian function and needs a way to compute numerical Jacobian if omitted. Fixed, I believe.
Changes in nlmrt version 2012-6.01
o Removed diagnostic printout of bdmsk in nlfb
Changes in nlmrt version 2012-4.15
o Added nlfb to allow functions for residual and Jacobian. These are developed from the expression for the residuals as a model in nlxb.
o Bounds now in wrapnls.
o Note misleading trace output in nls() runs with bounds.