To those interested in factor models you may find Matthieu Gomez's SparseFactorModels.jl <https://github.com/matthieugomez/SparseFactorModels.jl> useful.
Best Alan On Monday, 27 June 2016 02:04:02 UTC+1, [email protected] wrote: > > Sure, no problems. The gentlest introduction I know of (and it is still > fairly heavy reading) is Bai, Ng (2006) "Evaluating Latent and Observed > Factors in Macroeconomics and Finance" in the Journal of Econometrics. It > contains references to all the really heavy theoretical papers too if > you're interested. Probably also worth mentioning Bai, Ng (2002) > "Determining the Number of Factors in an Approximate Factor Model" in > Econometrica, as this material is necessary to consistently estimate the > dimension of the common factor space. > > If you don't have access to these journals, Serena Ng has pdfs and matlab > code for both papers at her homepage here: > http://www.columbia.edu/~sn2294/pub.html > > At some point or other I implemented the techniques in both papers in > matlab code too (Serena didn't have matlab code available at the time) so > let me know if you want a copy (I didn't get round to posting it on > file-exchange). If I had more free time I would probably have already made > a Julia package of this stuff, but kids = no free time :-) > > Cheers, > > Colin > > On Monday, 27 June 2016 10:22:46 UTC+10, Alex Williams wrote: >> >> Hey Colin - could you send a link or reference to that? Sounds like >> something I'd like to read up on. >> >> I'd really like to see a solid factor analysis implementation soon. As >> Diego said I think SciKitLearn.jl is the best stopgap option at the moment. >> On Jun 26, 2016 4:43 PM, <[email protected]> wrote: >> >>> I haven't seen anything yet on traditional common factor analysis by >>> maximum likelihood. Depending on your problem, you might be able to use >>> principal components instead which is implemented in >>> MultivariateStats.jl... e.g. in dual-asymptotic framework, simple >>> transformations of the first k principal components are consistent >>> estimators of the space-spanned by a k-dimensional common factor space. >>> >>> Cheers, >>> >>> Colin >>> >>> On Sunday, 26 June 2016 08:18:27 UTC+10, Jessica Koh wrote: >>>> >>>> Hello, >>>> >>>> Is factor analysis currently being developed? >>>> >>> -- >>> You received this message because you are subscribed to the Google >>> Groups "julia-stats" group. >>> To unsubscribe from this group and stop receiving emails from it, send >>> an email to [email protected]. >>> For more options, visit https://groups.google.com/d/optout. >>> >> -- You received this message because you are subscribed to the Google Groups "julia-stats" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. For more options, visit https://groups.google.com/d/optout.
