[oops, cc'd to r-sig-mixed by mistake. Sorry. Re-posting to r-sig-ecology.]
-------- Original Message -------- Subject: Fwd: Re: [R-sig-eco] cozigam Date: Wed, 13 Jun 2012 07:40:08 -0400 From: Ben Bolker <bbol...@gmail.com> To: r-sig-mixed-mod...@r-project.org <r-sig-mixed-mod...@r-project.org>, Mahnaz Rabbaniha <rab.mah...@gmail.com> [cc'ing back to r-ecology] -------- Original Message -------- Subject: Re: [R-sig-eco] cozigam Date: Wed, 13 Jun 2012 14:38:49 +0430 From: Mahnaz Rabbaniha <rab.mah...@gmail.com> To: Ben Bolker <bbol...@gmail.com> hi thanks for your answer for finding the relation i have try glm,gam and gam with smooth variable, but in all conditions the results shown unacceptable answer ( for example: R-sq.(adj) = 0.1 , Deviance explained = 18.9%) in base of contacts previous whit r - group and in base of zero in data,i decided to use cozigam,My awareness is low about it but i try different code in Liu,2010 . after the received mis mentioned above, i omitted depth and this code used: res <- cozigam(Clupeidae~s(temperature,salinity), constraint = "proportional", family = gaussian) result: [snip] > summary(res) Family: gaussian Parametric coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) -20.665505 13.904231 -1.486 0.1401 alpha -0.486186 0.207679 -2.341 0.0210 * delta1 0.010161 0.004781 2.125 0.0358 * Approximate significance of smooth terms: Edf Est.rank F p-value s(temperature,salinity) 20.81 29 8.77 <2e-16 *** --- Scale est. = 270.56 n = 132 what do you think? is it adequate for analyses ? do you have any suggest BMB> This is really too vague a question. You should do the usual things that are done with the results of any analysis: figure out what the parameters mean (e.g. by reading the JRSS COZIGAM paper: http://www.jstatsoft.org/v35/i11/paper ), look at the parameter estimates, their confidence intervals, predictions and see if they make sense, residuals and see if there are obvious violations of the statistical models (systematic patterns, variation in heterogeneity, etc.) On Wed, Jun 13, 2012 at 1:03 PM, Ben Bolker <bbol...@gmail.com <mailto:bbol...@gmail.com>> wrote: Mahnaz Rabbaniha <rab.mahnaz@...> writes: > i try to find regression between clupeidae,with temperature,salinity and > depth. the response variable is inclued many zero ( 86 from 133 observed) > > therefore i used this code : > > res <- cozigam(Clupeidae~s(temperature,salinity)+s(depth), constraint = > "proportional", family = gaussian) > > the result: > iteration = 2 norm = 1.001743 > iteration = 3 norm = 0.3377464 > iteration = 4 norm = 9.172232e-05 > > ========================================== > estimated alpha = -0.5337883 ( 0.1789113 ) > estimated delta = -0.0009891505 ( NaN ) > ========================================== > > Warning message: > > In sqrt(V.theta[2, 2]) : NaNs produced > > what is exactly meaning? You're probably not getting answers to your repeated posts because you're not providing a reproducible example ( http://tinyurl.com/reproducible-000 ) and not giving very much detail about your problem. I strongly suspect that your model is too complex for your data: a general rule of thumb is that you need about 10 observations per parameter estimated. It's a bit hard to count in this case for two reasons -- zeroes are relatively uninformative (so each zero counts for less than one 'effective' observation), and it's a little hard to count parameters for penalized smooth terms -- but I think you can't really expect to fit a two-way smooth term on temperature and salinity *and* a smooth term on depth ... the example in the COZIGAM JRSS paper (referenced in the help) fits a model of about the same complexity to 274 data points with 84 zero catches -- somewhere between 3 and 4 times as much data as you have. Most narrowly, the program is trying to estimate the standard error of the parameter by inverting the matrix of second derivatives, and failing because the surface is too flat, or too strongly correlated, or some similar problem. _______________________________________________ R-sig-ecology mailing list R-sig-ecology@r-project.org <mailto:R-sig-ecology@r-project.org> https://stat.ethz.ch/mailman/listinfo/r-sig-ecology _______________________________________________ R-sig-ecology mailing list R-sig-ecology@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-ecology