[R] Frustration to get help R users group

[Jeff Newmiller]

This is dangerously close to a statistics theory question, which would be off-topic on this list. In any event, your example is definitely not reproducible (no sample data) [1]. Now might also be a good opportunity for you to read the Posting Guide mentioned at the bottom of every message on this list.

[1] http://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example
---------------------------------------------------------------------------
Jeff Newmiller                        The     .....       .....  Go Live...
DCN:<jdnewmil at dcn.davis.ca.us>        Basics: ##.#.       ##.#.  Live Go...
                                      Live:   OO#.. Dead: OO#..  Playing
Research Engineer (Solar/Batteries            O.O#.       #.O#.  with
/Software/Embedded Controllers)               .OO#.       .OO#.  rocks...1k
--------------------------------------------------------------------------- 
Sent from my phone. Please excuse my brevity.

Champak Ishram <champak.ishram at gmail.com> wrote:

>Dear  R users/developers
>I requested help to solve the problem of formulating Multivariate
>Sample
>selection model by using Full Information Maximum Likelihood
>(FIML)estimation method. I could not get any response. I formulated the
>following code of FIML to analyse univariate sample selection problem.
>Would you please advise me where is my problem
>
>library (sem)
>library(nrmlepln)
>
>Selection equation
>ws = c(w1, w2, w3)
>
># values of dependent variables in selection equations are binary  (1
>and 0)
>zs = c(z1, z2, z3, z4, z5)
># z1, z2, z3 continuous and z4 and z5 dummies explanatory variables in
>selection equation
>
>Level equation (extent of particular option use)
>ys = c(y1, y2, y3)
># values of dependent variables are percentage with some zero cases
>xs = c(x1, x2, x3, x4, x5)
># x1, x2, x3 continuous and x4 and x5 dummies dependent variables.
>
>#Note: The variables in both selection and level equations are mostly
>same.
>
>
>                    #Selection model
>
>models1 = 'w1 ~ 1 + zs'
>
> # Level model
>model1 = 'w1 ~ 1 + zs|y1 ~ 1 + xs'
>
>fit.fiml = sem(model1, data=MyRdata, estimator="Fiml") # not sure "ML"
>or
>"Fiml"
>summary(fit.fiml)
>
>I greatly appreciate your help.
>
>Advance thank you.
>Regards
>Champak Ishram
>
>	[[alternative HTML version deleted]]
>
>______________________________________________
>R-help at r-project.org mailing list
>https://stat.ethz.ch/mailman/listinfo/r-help
>PLEASE do read the posting guide
>http://www.R-project.org/posting-guide.html
>and provide commented, minimal, self-contained, reproducible code.