I'm looking for statistical rather than machine learning packages, in the sense that I'd need standard errors and covariates of the regressors, and various other standard statistics (similar to GLMs). The model I'm looking at is fairly simple, and almost a GLM:
p(y = 1 | x) = (1-pl) Phi((x - mu)/sig) + pl pb where Phi is the standard cumulative Gaussian. I want to fit the above by least squares regression. I could code the whole thing myself, but as nonlinear regression is such a standard problem, I was wondering if a package exists that saves me from having to do so. Thanks, Jan On Thursday, 26 May 2016 18:44:09 UTC-4, Tom Breloff wrote: > > There's lots of potential options. Can you specify your problem a little > more? What type of data? How non-linear? Are we fitting a polynomial? SVM? > ANN? Online vs batch? How much noise? What sort of stats do you want? > > On Thursday, May 26, 2016, Jan Drugowitsch <[email protected] <javascript:>> > wrote: > >> Hi all, >> >> I have some nonlinear regression problems that I'd like to solve. >> Unfortunately, NLreg.jl doesn't seem to work on my Julia 0.4.5 >> installation, but instead fails on the README example code with >> >> julia> const sd1 = readtable(Pkg.dir("NLreg","data","sd1.csv.gz")); >> >> >> julia> nl = fit(BolusSD1(CONC ~ TIME, sd1)) >> WARNING: [a,b] concatenation is deprecated; use [a;b] instead >> in depwarn at deprecated.jl:73 >> in oldstyle_vcat_warning at /Applications/Julia-0.4.5.app/Contents/ >> Resources/julia/lib/julia/sys.dylib >> in call at /Users/jandrugowitsch/.julia/v0.4/NLreg/src/plreg.jl:119 >> in fit at /Users/jandrugowitsch/.julia/v0.4/NLreg/src/plreg.jl:204 >> while loading no file, in expression starting on line 0 >> ERROR: type Array has no field data >> in gpinc at /Users/jandrugowitsch/.julia/v0.4/NLreg/src/plreg.jl:143 >> in gpfit at /Users/jandrugowitsch/.julia/v0.4/NLreg/src/plreg.jl:159 >> in fit at /Users/jandrugowitsch/.julia/v0.4/NLreg/src/plreg.jl:204 >> >> >> In general, NLreg.jl hasn't been updated since 2014. Are there any more >> up-to-date Julia packages for nonlinear regression? >> >> I know that I could always use optimizers, but then I won't get all the >> extra statistics that I would need. >> >> Thanks, >> Jan >> >
