similar to: predict.nls confidence intervals

Hi - I am fitting a probit model using glm(), and the deviance and residual degrees of freedom are different depending on whether I use a binary response vector of length 80 or a two-column matrix response (10 rows) with the number of success and failures in each column. I would think that these would be just two different ways of specifying the same model, but this does not appear to be the case.

Hello Is it possible to take advantage of copy-on-write implemented in btrfs if all bricks are stored on it? If not is there any other mechanism (in glusterfs) which supports CoW? regards -- Maciej Ga?kiewicz Shelly Cloud Sp. z o. o., Sysadmin http://shellycloud.com/, macias at shellycloud.com KRS: 0000440358 REGON: 101504426 -------------- next part -------------- An HTML attachment was

Hi, I am trying to send emails out using ActionMailer. Currently, the console shows that everything is sending out correctly, but I am not actually receiving any emails. Thanks in advance, Shelly --~--~---------~--~----~------------~-------~--~----~ You received this message because you are subscribed to the Google Groups "Ruby on Rails: Talk" group. To post to this group, send email

Hello- I understand that log-likelihoods are bound to differ by constants, but if i estimate AIC for a set of simple nested linear models using the following 4 methods, shouldn't at least two of them produce the same ordering of models? in R: extractAIC AIC in S-PLUS: AIC n*log(deviance(mymodel)/n) + 2*p I find it troubling that these methods all give me different answers as to the best

On 16 October 2013 13:55, Daniel P. Berrange <berrange@redhat.com> wrote: > > Sounds like a host mis-configuration related to kernel bridge support > to me. > Could you tell me what might be mis-configured? I am using kernel 3.10.11, modules openvswitch, bridge, stp and llc are loaded. regards -- Maciej Gałkiewicz Shelly Cloud Sp. z o. o., Sysadmin http://shellycloud.com/,

As a simple example, I want to find minimum value for x^2, but it can't be obtained by: f<-function(x)x^2 optimize(f,lower=-1,upper=1) What are other methods to deal with this? I tried DEoptim, still doesn't work. Any suggustions will be extremely helpful! THanks! Shelly -- View this message in context: http://r.789695.n4.nabble.com/Optimization-problem-tp4663821.html Sent from

Hi I am using Libvirt 1.1.2 with Openstack Havana (RC2, nova-network) and openvswitch 1.4.2+git20120612-9.1. Libvirt vif driver ( nova.virt.libvirt.vif.LibvirtGenericVIFDriver) generates config likes this: <interface type='bridge'> <mac address='fa:16:3e:44:30:a4'/> <source bridge='br0'/> <model type='virtio'/>

On 2 July 2013 09:58, Martin Kletzander <mkletzan@redhat.com> wrote: > I'd say this is a problem with sasl, nothing else. "No mechanism found" > may mean that libraries for configured mechanism aren't found or unknown > mechanism is being requested. I doubt that access to those libraries > would be a permisison problem, but you might be missing some >

I am using R 2.3.0, Is there a way to get prediction intervals using predict.gls? Any ideas would be appreciated. thanks, Spencer On 11/2/06, Frank McCown <fmccown@cs.odu.edu> wrote: > > I was wondering if anyone knows who should be contacted to add to the R > user-contributed documentation at > > http://www.r-project.org/other-docs.html > > There doesn't

Hi, I have a dataset with the following properties: Y_i ~ N(mu_i, theta * (mu_i)^2) ln(mu_i) = B'Xi theta and beta's are the parameters here. I want to come up with a model to fit the data with the above property and test that model on the built in R dataset quine. Does nls() make sense in this case? Or is there any existing R package which can fit this model? -Shelly -- View

Hi all! After fitting a mixed effects model to repeated measurements data set, and after several unsuccessful atempts to make a simple plot of the confidence interval for the fitted model, I gave up and now I am asking for help in this useful list. Could anyone be so kind to give me some code lines in order to make a plot of the fitted equation and the correspondent confidence interval?

Hi, I´m trying to plot a nonlinear regresion with the confidence bands for the curve obtained, similar to what nlintool or nlpredci functions in Matlab does, but I no figure how to. In nls the option is there but not implemented yet. Is there a plan to implement the in a relative near future? Thanks in advance, Florencio La información contenida en este e-mail y sus ficheros adjuntos es

Dear R graphics gurus, Another question about lattice graphics. This time I would like to plot means and confidence intervals by group factor in a lattice graph. I can not find any working lattice examples. Maybe a custom panel function is the answer, but that is a bit beyond me for now. The individual plots within the lattice graph could look like this: # Example with confidence intervals

Hello I have a question about live migration when libvirt requires sasl authentication. I have managed to configure remote access for user nova with sasl enabled (credentials stored in auth.conf - https://review.openstack.org/#/c/12706/). It looks like live migration do not use these credentials at all. What is more it thinks that sasl is not not configured: 2013-07-01 09:49:09.317+0000: 17997:

Moved from r-help: On Thu, 14 Aug 2003 09:08:26 -0700, Spencer Graves <spencer.graves@pdf.com> wrote : >p.s. The following command in S-Plus 6.1 seems to work fine but >produces an error in R 1.7.1: > >nls(y~a, data=tstDf, start=list(a=1)) >Error in nlsModel(formula, mf, start) : singular gradient matrix at >initial parameter estimates This looks like a bug in

Dear All I am quite new to R and would appreciate some help fitting 95% confidence intervals to a nls function. I have the data DOY CET 90 5.9 91 8 92 8.4 93 7.7 95 6.6 96 6.8 97 7.1 98 9.7 99 12.3 100 12.8 102 11 103 9.3 104 9.8 105 9.9 107 7.7 110 6.2 111 5.9 112 5.9 113 3.4 114 3.5 116 3.3 117 5.4 118 6.3 119 9.7 120 11.2 121 7.3 124 7.8 etc I am trying to use some code that has been

I have data that looks like O.lengthO.age 176 1 179 1 182 1 ... 493 5 494 5 514 5 606 5 462 6 491 6 537 6 553 6 432 7 522 7 625 8 661 8 687 10 704 10 615 12 (truncated) with a simple VonB growth model from within nls(): plot(O.length~O.age, data=OS) Oto = nls(O.length~Linf*(1-exp(-k*(O.age-t0))), data=OS, start=list(Linf=1000, k=0.1, t0=0.1), trace=TRUE) mod <- seq(0, 12)

for unweighted fits using `nls' I compute confidence intervals for the fitted model function by using: #------------------- se.fit <- sqrt(apply(rr$m$gradient(), 1, function(x) sum(vcov(rr)*outer(x,x)))) luconf <- yfit + outer(se.fit, qnorm(c(probex, 1 - probex))) #------------------- where `rr' contains an `nls' object, `x' is the independent variable vector, `yfit'

Hi, Does anyone know how to compute the confidence prediction intervals for a nonlinear least squares models (nls)? I was trying to use the function 'predict' as I usually do for other models fitting (glm, lm, gams...), but it seems that se.fit, and interval computation is not implemented for the nls... Cheers Enrique ~~~~~~~~~~~~~~~~~~~~~~~~~~~ Fisheries Research Services, Marine

Hi all I have fitted a model usinf nls function to these data: > x [1] 1 0 0 4 3 5 12 10 12 100 100 100 > y [1] 1.281055090 1.563609934 0.001570796 2.291579783 0.841891853 [6] 6.553951324 14.243274230 14.519899320 15.066473610 21.728809880 [11] 18.553054450 23.722637370 The model fitted is: modellogis<-nls(y~SSlogis(x,a,b,c)) It runs OK. Then I calculate