similar to: - detecting outliers

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)

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

Hello all, I would like to get parameter estimates for different models. For one of them I give the code in example. I am estimating the parameters (i,j and k) with the nls function, which sees the error distribution as normal, I would however like to do the same as nls with the assumption that the errors are poisson distributed. Is there a way to do this with R? Are there packages designed

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, I am new to R and I would like to get your help in finding 'outliers'. I have mvoutlier package installed in my system and added the package . But I not able find a function from 'mvoutlier' package which will identify 'outliers'. This is the sample list of data I have got which has one out-lier. 11489 11008 11873 80000000 9558 8645 8024 8371 It will

Dear list, I'm forwarding these 2 messages as suggested by the package developer. My system is > sessionInfo() R version 2.9.0 (2009-04-17) i486-pc-linux-gnu on Ubuntu 8.04, with r-base-core, r-base-dev and r-recommended installed from binaries through Synaptic. I normally install the rest of packages using install.packages() from within R (started from an xterminal by su) Agus

Hi R experts :) I'm trying to carry out a survival model on my data, but I am unsure of whether it's appropriate or if I should do something specific in regards to hazard. My data is time to death by predator where I have 8 prey and one predator in the setting. This means that two prey can't possibly die at the same time and I can't quite get my head around how to include this in

I'm fairly new to R, and I'm trying to write out a population model that satisfies the following; the system consists of s species, i= 1, 2,...,s network of interactions between species is specified by a (s x s) real matrix, C[i,j] x[i] being the relative population of the "ith" species (0 =< x[i] =< 1, sum(x[i]=1) the evolution rule being considered is as follows;

I haven't seen this cryptic warning before: > update.views('Robust') Warning message: In update.views("Robust") : The following packages are not available: covRobust, distr, FRB, MASS, mblm, multinomRob, mvoutlier, quantreg, RandVar, rgam, RobAStBase, robfilter, RobLox, RobRex, robust, RobustAFT, robustbase, ROptEst, ROptRegTS, rrcov, sandwich, wle >

Dear R-users, I am currently modifying a previously developed predator prey model and was curious if there was a way to add in a disturbance to the model (let's say at time t=100). The disturbance can be the introduction of 40 prey (N=40) and 10 predators (Pred = 10). I would like to see my model go from a state of equilibrium (up to t = 99), show this disturbance (at t = 100) and then

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'') >

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

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

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, I wonder if anyone can help me with specifying a right model for my analysis. I am a beginner to lme methods and though have spent already many hours studying from various books an on-line helps, I was unfortunately not able to find a solution to my problem on my own. Data structure: I studied escape behavior of three species of a prey to a predator. The prey specimens (many) were in a

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 > }

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 everybody, I am wondering how i can add a "stretch" color bar / legend to a graph that uses colorBrewer to define the colors in it. I will try to explain my graph, but i also uploaded it at: ftp://ftpext.usgs.gov/pub/er/fl/st.petersburg/Monica_pal/ The file is: robcor_training_pca.pdf - i will also attach this file in case some people accept attachments. So i took apart the