similar to: regression for poisson distributed data

Hi all, I have some problems with the mle2 function > RogersIIbinom <- function(N0,attackR3_B,Th3_B) {N0-lambertW(attackR3_B*Th3_B*N0*exp(-attackR3_B*(24-Th3_B*N0)))/(attackR3_B*Th3_B)} > RogersII_B <- mle2(FR~dbinom(size=N0,prob=RogersIIbinom(N0,attackR3_B,Th3_B)/N0),start=list(attackR3_B=1.5,Th3_B=0.04),method="Nelder-Mead",data=dat) Error in dbinom(x, size, prob, log)

Hello all, I am estimating parameters for regression functions on experimental data. Functional response of Rogers type II. I would like to know which points of my dataset are outliers. What is the best method to do this with R? I found a method via R help, but would like to know if there are better methods for my purpose. Here is the script I us now: library("mvoutlier") dat

Hi all, When I try to estimate the functional response of the Rogers type I equation (for the mle2 you need the package bbmle): > RogersIbinom <- function(N0,attackR2_B,u_B) {attackR2_B+u_B*N0} > RogersI_B <- mle2(FR~dbinom(size=N0,prob=RogersIbinom(N0,attackR2_B,u_B)/N0),start=list(attackR2_B=4.5,u_B=0.16),method="Nelder-Mead",data=data5) I get following error message

Hi all, I would like to predict some values for an nls regression function (functional response model Rogers type II). This is an asymptotic function of which I would like to predict the asymptotic value I estimated the paramters with nls, but can't seem to get predictions for values of m choice...... This is my script: RogersII_N <-

Hi all, I am doing nls regression of the Rogers type III equation. However I can't find good starting values and keep getting the error messages: "Missing value or an infinity produced when evaluating the model" OR "singular gradient matrix at initial parameter estimates" Is there a way to automatically check different starting values and give a list of values for each

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 all, I have a following problem: - Remus network buffering doesn''t work. It seems to be because of no vif is reported by the function server.xend.domain on line 29 of /usr/local/lib/python2.7/dist-packages/xen/remus/vm.py (seen using pdb) : 27 if domid: 28 try: 29 self.dominfo = server.xend.domain(domid, ''all'') >

Hello, I''ve recently setup a Linux Dom0 with a 3.0.17 kernel and Xen 4.1.2, and since the 3.x series doesn''t have blktap support I''m using qdisk to attach raw images. I''ve been playing with small images, something like 1GB, and everything seemed fine, speed was not fantastic but it was ok. Today I''ve set up a bigger machine, with a 20GB raw hdd and the

Dear R Help, I read through the archives pretty extensively before sending this email, as it seemed there were several threads on using predict with GLM. However, while my issue is similar to previous posts (cannot get it to predict using new data), none of the suggested fixes are working. The important bits of my code: set.seed(644) n0=200 #number of observations

Hi, I am new in R and stumbled on a problem my (more experienced) friends can not help with with. Why isnt this code working? The function is working, also with the loop and the graph appears, only when I build another loop around it (for different values of p) , R stays in a loop? Can't it take more then 2 loops in one program? powerb<-function(x,sp2,a,b,b1,m) {

Hi all, I've been working on a backend of our architecture and noticed llvm performs following combining although one of operands is FrameIndex. Combining: t114: i64 = add FrameIndex:i64<0>, Constant:i64<56> Creating new node: t121: i64 = or FrameIndex:i64<0>, Constant:i64<56> ... into: t121: i64 = or FrameIndex:i64<0>, Constant:i64<56> This

I am trying to define a general R function that has a function as the output that depends on the user's input arguments (this may make more sense by looking at the toy example below). My real use for this type of code is to allow a user to choose from many parameterizations of the same general model. My "issue" is that when I compile a package with this type of code in it I get a

Dear list, I have the function (as a simple example, which is actually part of a larger function) pres.test<-function(N0=N0, N1=N1) { dt<-5 r<-log(N1/N0)/dt r } which calculates the annual growth rates in a population Where N0 is the population classified into age intervals, say 5 years, at time=1995, and N1 is the population by 5 year age classes at time=2000.

Hi All, Apologies for the simplicity of my question, but I would be grateful for any advice. Thanks I'm trying to put the output from a for loop into a data frame, however I have not been successful. The steps I have taken are: *R-code:* >for (k in 1:(nt-1-n0) ){ > n<- n0-1+k > lam=n/nt > Q=x[n] > output1<-data.frame(cbind(k,n,lam,Q)) > output1 > }

I've got a covariance matrix that I'd like to index using the dimnames: > vcov1 n0 x0 s n1 n2 n0 82.43824759 1.839505e-02 -4.975196e-01 2.882394e+03 -2.615986e-01 x0 0.01839505 6.134010e-03 -7.695922e-04 -6.373946e+01 6.086321e-03 s -0.49751964 -7.695922e-04 9.638943e-03 3.406594e+02 -3.173671e-02 n1 2882.39407745

Bill Wendling wrote: > On Sep 30, 2010, at 2:13 AM, Heikki Kultala wrote: > >> Bill Wendling wrote: >>> On Sep 29, 2010, at 12:36 AM, Heikki Kultala wrote: >>> >>>> On 29 Sep 2010, at 06:25, Heikki Kultala wrote: >>>> >>>>> Our architecture has 1-bit boolean predicate registers. >>>>> >>>>> I've

On Wed, Jul 27, 2011 at 3:50 PM, Matt Johnson <johnso87 at crhc.illinois.edu> wrote: > Hi Eli, > > On 07/27/2011 04:59 PM, Eli Friedman wrote: >> >> On Wed, Jul 27, 2011 at 2:28 PM, Matt Johnson >> <johnso87 at crhc.illinois.edu>  wrote: >>> >>> Hi All, >>>     I'm writing a backend for a target which only supports 4-byte,

I'm running into lots of problems with this call back. Mostly the problem occurs because this callback is used before types are legalized. However, the code generator does not have a 1-1 correspondence between all LLVM types and the codegen types. This leads to problems when getSetCCResultType is passed in an invalid type, but has a valid LLVM type attached to it. An example is <3 x

Hi, Is there a way to stack bars in a barchart as well as "beside" bars for the same treatment? eg.... I have one barchart like this: bio<-matrix(c(10,23,9,25),nrow=2,byrow=T) ntreat<-c("n0","n96") colnames(bio)<-ntreat barplot(bio,beside=T) now i want a similar barchart but with stacked bars:

if (N0.getOpcode() == ISD::SETCC && (LegalOperations || (!LegalOperations && VT.isPow2VectorType()))) But the comment right after it is: // sext(setcc) -> sext_in_reg(vsetcc) for vectors. // Only do this before legalize for now. if (VT.isVector() && !LegalOperations) { So, these optimizations are never safe in the general case if we can't