[Developers] Check Release procedure

Wed Apr 4 14:11:44 PDT 2012

Thanks Dave, I've always tried to keep it simple.  As John Sibert often
says to me
that I should use the KISS principle (Keep It Simple Stupid).  The main
objective is to
continually improve the code for the end users.  I will not
allow unnecessary processes
hindering developers or the main objective.

The release procedure is just an informal checklist to ensure that I don't
forget to do
something.  It is procedure that was used for past releases. I just wanted
to let everyone
who was curious know the procedure used.

Anyhow, thank you again for your continued evolvement with the project.  I
look forward
to reading your opinions and receiving bug fixes.

Cheers,
Johnoel

On Wed, Apr 4, 2012 at 10:26 AM, dave fournier <davef at otter-rsch.com> wrote:

> **
> On 12-04-04 09:55 AM, Ian Taylor wrote:
>
> I pretty sure that you (almost) all think I'm unreasonable.   I've been
> told (too many times) that R was designed by a bunch of geniuses.  Here is
> a typical attempt to make a trivial change to a model
> by one of the greatest heroes of open source.
>
> On Thu, Sep 30, 2010 at 3:29 PM, Douglas Bates <bates at stat.wisc.edu <https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models>> wrote:
> >* Unfortunately an nlmer model is not appropriate for a binary response,*>* because it doesn't appropriately weight the residuals.*>**>* Incorporating a non-zero guessing parameter requires a generalized*>* nonlinear mixed model if you need to estimate the guessing parameter.*>* The long term plan is to allow such a model.  This is the reason that*>* Martin and I worked on factoring out the internal code dealing with*>* different kinds of models for the expected response.  Nonlinear models*>* affect these in one way and generalized linear models in another so*>* you need to chain these effects.*>**>* For the particular case that Robert is considering, in which the*>* guessing parameter is fixed at 0.33 I think it may be possible to use*>* the mafc.logit link from the psyphy package with lme4a, the*>* development version of lme4.  I am currently installing the necessary*>* packages to see if I can make it work.  My thanks to Robert for making*>* the data available so we can test it.*
> It wasn't as easy as I had hoped it would be.  I'm getting an error
> when evaluating the linkfun (and, presumably, will get such an error
> for all the other functions in the family).  It probably has to do
> with the environment in which the function is evaluated in that it
> can't see the value of 'm'.
>
> I'm not sure if I will be able to fix it in a reasonable amount of
> time (I should be grading assignments from one of my classes right
> now).
>
> Actually the whole design of the glm families should be reconsidered
> but we'll save that for another time.
>
> >* On Mon, Sep 27, 2010 at 11:25 AM, Manuel Morales*>* <Manuel.A.Morales at williams.edu <https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models>> wrote:*>>* I found this link doing a search for your error message on Google:*>>* https://stat.ethz.ch/pipermail/r-sig-mixed-models/2007q4/000408.html*>>**>>* Following the recipe:*>>* grModel <- function(x,y,a,b,c,d) .33 + .67*(exp(log(x)*a+y*b+log(x)*y*c*>>* + d))/*>>*  (1+exp( log(x)*a + y*b +log(x)*y*c + d))*>>**>>* grModg <- deriv(body(grModel), namevec = c("a","b","c","d"),*>>* function.arg=grModel)*>>**>>* mod3 <- nlmer(Correct~grModg(Concentrat,Test,a,b,c,d)~(Test|Code),*>>*              start = c(a = 0.115, b=-0.1, c=0.65, d=-3),*>>*              data = rawdata)*>>* Which appears to work.*>>**>>* My messages haven't been posted to R, so you may want to post again with*>>* this solution if it works for you.*>>**>>* Best,*>>**>>* Manuel*>>**>>* On Mon, 2010-09-27 at 15:54 +0200, Robert Miller wrote:*>>>* Hello everyone,*>>>**>>>* Recently i tried to predict the discrimination probability of a chemosignal*>>>* by its concentration and an experimental manipulation factor (term:*>>>* concentration*x + test*b + concentration*test*c + d) with nested factor*>>>* "manipulation" within "participants". For statistical analysis i needed to*>>>* incorporate a fixed guessing probability into my model (similiar to a 3-PL*>>>* IRT model) resulting in the following equation:*>>>**>>>* P(correct) = 0.33 + 0.67*(exp(term)/(1 + exp(term)))*>>>**>>>* As i found no way to do so via the glmer()-function of the lme4-package, i*>>>* tried to use nlmer() but unfortunately even the simplest analysis with just*>>>* the concentration factor and intercept resulted in cryptic error messages.*>>>**>>>* Syntax:*>>>* library(lme4)*>>>* rawdata <- read.csv2("http://dl.dropbox.com/u/7147679/AND_data.csv")*>>>**>>>* mod1 <- glmer(Correct ~ log(Concentrat) * Test + (Test|Code), family =*>>>* binomial, data=rawdata) #works fine but is inappropriate*>>>* mod2 <- nlmer(Correct ~ .33 + .67*(exp(log(Concentrat)*a+d))*>>>* /(1+exp(log(Concentrat)*a+d)) ~ (Test|Code), start = c(a = 0.1, d = -3),*>>>* data = rawdata) #doesnt work*>>>* mod3 <- nlmer(Correct ~ .33 + .67*(exp(log(Concentrat)*a + Test*b +*>>>* log(Concentrat)*Test*c + d))/(1+exp( log(Concentrat)*a + Test*b +*>>>* log(Concentrat)*Test*c + d)) ~ (Test|Code), start = c(a = 0.115,b = -0.05,*>>>* c= 0.065, d= -3), data = rawdata) #doesnt work either*>>>**>>>* Even without specifying random effects nls() doesnt work, but brute force*>>>* ML-parameter estimation on the aggregated data produces reasonable results.*>>>**>>>* Right now I'm quite desperate and would appreciate any help.*>>>* Thank you*>>>* Robert Miller*>>>**>>>* _______________________________________________*>>>* R-sig-mixed-models at r-project.org <https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models> mailing list*>>>* https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models*>>**>>* --*>>* http://mutualism.williams.edu*>>**>>* _______________________________________________*>>* R-sig-mixed-models at r-project.org <https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models> mailing list*>>* https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models*>>**>**
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> I like the formality and the fact that this is written down.
> In a case where a bug is found after release, what would happen: a repeat
> of the full procedure, a shorter testing phase for the bug fix, or what?
>  -Ian
>
> On Wed, Apr 4, 2012 at 9:49 AM, Arni Magnusson <arnima at hafro.is> wrote:
>
>> I have updated the heading to "Annual Release", and added a couple of
>> explanatory sentences at the top and bottom of the page.
>>
>> Thanks for posting this very useful reference, Johnoel.
>>
>> Arni
>>
>>
>>
>>
>> On Wed, 4 Apr 2012, John Sibert wrote:
>>
>>  It looks rather formal.
>>>
>>> How frequently would there be a new release?
>>>
>>>
>>>
>>>
>>   On Wed, 3 Ap 2012, Johnoel Ancheta wrote:
>>>
>>>  http://admb-project.org/developers/admb-release-procedure
>>>>
>>>
>>>  _______________________________________________
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>> Developers at admb-project.org
>> http://lists.admb-project.org/mailman/listinfo/developers
>>
>
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