similar to: New package: logmult (log-multiplicative models)

Hi! Some time ago, I replaced calls to library() with calls to requireNamespace() in my package logmult, in order to follow the new CRAN policies. But I just noticed it broke jackknife/bootstrap using several workers via package parallel. The reason is that I'm running model replicates on the workers, and the formula includes non-standard terms like Mult() which are provided by gnm. If gnm

Hi Milan, I expect I may be able to do something about the way the terms are evaluated, to ensure the evaluation is done in the gnm namespace (while still ensuring the variables can be found!). In the meantime, I think the following will work: Mult <- gnm::Mult f <- Freq ~ Eye + Hair + Mult(Eye, Hair) gnm::gnm(f, family=poisson, data=dat) Hope that helps, Heather On Wed, Apr 29, 2015,

The NEWS for R 2.3.0 states that "R CMD check works for packages whose package name is different from the directory name in which it is located." However that hasn't been my experience. I ran R CMD check on package sources located in a directory with the same name as the package and it worked as expected. Then I renamed the directory and tried again. The first attempt got stuck

Hi all I want to construct a generalised nonlinear model (binomial family) using gnm, of the form: Response = a + b variable1 + c variable2 + d variable3 - d b variable4 - d c variable5, with the parameters b, c, and d appearing more than once. Hence, I think I need to use a custom nonlin function with gnm. One of my predictor variables is categorical, so I have created a dummy variable for

In checking my vcdExtra package, the following NOTE newly appeared (R-Forge, using R version 3.0.1 Patched (2013-08-20 r63635)) Package in Depends field not imported from: ?gnm? These packages needs to imported from for the case when this namespace is loaded but not attached. In the DESCRIPTION file, I have Depends: R (>= 2.10), vcd, gnm (>= 1.0.3) In NAMESPACE: # we are a vcd

Hi all, I'm trying to fit a nonlinear (logistic-like) regression, and I'd like to get some recommendations for which package to use. The expression I want to fit is something like: y ~ A * exp(X * Beta1) / (1 + exp(-(x + X * Beta2 - xmid)/scal)) Basically, it's a logistic function, but I want to be able to modify the saturation amplitude by a few parameters (Beta1) and shift the

I'm pleased to announce the release of the vcdExtra package, v. 0.5-0 from R-Forge to CRAN, on its way to a CRAN server near you. vcdExtra was originally designed to serve as a sandbox for introducing extensions of mosaic plots and other visualizations for categorical data, particularly those that apply to (poisson surrogate) loglinear models fitted using glm() and related, generalized

In previous versions of the gnm package, the terms component of "gnm" objects had a "classID" attribute. This caused problems when used with str as the following simple example illustrates: > x <- 1 > attr(x, "classID") <- "type1" > str(x) Class 'type1' Class 'type1' Class 'type1' Class 'type1' Class

Dear All, 1)Can I use lm() to fit more than one response in single expression. e.g data is a matrix of these variables R1 R2 R3 X Y Z 1 2 1 1 2 3 .... Now i wnat to fit R1:R3 ~ X+Y+Z. 2) How can i use Singular Value decomposition (SVD) as an alternate to lsq. Regards,

Hi, I am trying to use optim to solve a heavy calibration problem. I supply the parameters in vector form. But before entering my target The call is simply: optim(par = parameters, fn = SumLSQ, method = "Nelder-Mead") the function SumLSQ is simply: SumLSQ<-function(parameters, data = timeseries){ print("sumLSQ") nbseries =

On 21/03/2010, at 10:38 PM, Skip Montanaro wrote: >> I don't know anything about Solaris, but your paste doesn't actually >> contain any errors, just warnings (unless I'm reading "ld: warning: >> relocation error:" wrong). It might help to run make without -j until >> it fails, and then use `make VERBOSE=1` to print the exact commands >>

Hi everyone, I'm trying to perform the following regressions in order to compare linear vs. sigmoidal fit of the relationship between my dependent variable (y) and one explaining parameter (x2), both including the confounding effects of a third variable (x1): quasi-pois-lin <- glm(y ~ x1 + x2, family = quasipoisson(link="identity"), data=fit) quasi-pois-sig <- gnm(y ~ x1 +

Hi, I am quite new to R and would like to do nonlinear regressions with Poisson distributed data. I would like to estimate paramters of an equation of this type: FR = [c*NO * exp(a+b*NO)] / [(c+NO)*(1+exp(a+b*NO))] a,b and c are parameters, NO are input values I found both the gnm and gnlr3 function which should be able to do this regression but I can't manage to make it work. How can I

Hi everyone! In a package I'm developing, I have created a custom function to get jackknife standard errors for the parameters of a gnm model (which is essentially the same as a glm model for this issue). I'd like to add support for bootstrap using package boot, but I couldn't find how to proceed. The problem is, my data is a table object. Thus, I don't have one individual per

I received the following email note re: the vcdExtra package > A vcd update has shown that packages TIMP and vcdExtra are not > declaring their dependence on colorspace/MASS: see > > http://cran.r-project.org/web/checks/check_results_vcdExtra.html But, I can't see what to do to avoid this, nor understand what has changed in R devel. Sure enough, CRAN now reports errors in

Hi all, I'm not familiar with R programming and I'm trying to reproduce a result from a paper. Basically, I have a dataset which I would like to model in terms of successive increments, i.e. (y denote empirical values of y) y_1 = y1, y_2 = y1 + delta1, y_3 = y1 + delta1 + delta2. ... y_m = y1 + sum_2^m delta j where delta_j donote successive increments in the y-values, i.e. delta

Hello, I am attempting to fit a non-linear model (Von Bertalanffy growth model) to fish length-at-age data with the purpose of determining if any of the three parameters differ between male and female fish. I believe that I can successfully accomplish this goal assuming an additive error structure (illustrated in section 1 below). My trouble begins when I attempt this analysis using a model

I have searched through the archives, and on google, but I was not able to find anything on this type of error. Although the docs say Wine only supports x86, I found some articles where people have gotten it to work. Basically the error is: gcc -c -I. -I. -I../../include -I../../include -g -fPIC -D__WINE__ -D_ADVAPI32_ -D_REENTRANT -I/usr/openwin/include -o advapi32.spec.o advapi32.spec.c|head

Hello! I would like to ask whether the seasonality implemented in arima() is additive or multiplicative? I searched a lot, but I could not find an answer to that question, although it has been asked other times too. Thank you very much for your attention. Regards, Martin

I posted on this topic to r-help, but never got a sufficient answer, so I'm reposting here. [Env: R 2.11.1, Win Xp, using Eclipse/StatET] In a package I'm working on, I want to create as.matrix() and as.array() methods for a particular kind of object (log odds ratios). These are returned in a loddsratio object as the $coefficients component, a vector, but really reflect an underlying