search for: emb7

Hi all, Forgive me if this is an obvious one.... I want to make a plot of confidence intervals from an lmList object with a collection of simple linear models (lm(y~x)) using: plot(intervals(mylmList)) and sort the plot by increasing mean values for the intercept. Is there an easy way of doing this? I've tried the "order()" and "sort.list()" functions, but I suspect

Hello, Once again, I posted a message without a subject line. Sorry.... here is the question again. Is there a simple way to modify the circ.mean function in the CircStats package to include a vector of weights to obtain a weighted average angle? Thanks! Martin -- Martin Biuw Sea Mammal Research Unit Gatty Marine Laboratory, University of St Andrews St Andrews, Fife KY16 8PA Scotland Ph:

Hello, I''m trying to fit a linear mixed effects model of the form: lme(y ~ x * Sex * Year, random=x|subject) where Sex and Year are factors with two and three levels respectively. I want to compare the fixed effects for each level to the overall mean, but the default in R is to compare to the first level. This can be changed by adding the term -1 to the righthand side of the model

Hi, Sorry if this is an obvious one, but is there a simple way to modify the lm function to test whether a slope coefficient is significantly different from 1 instead of different from 0? Thanks, Martin Martin Biuw SEA MAMMAL RESEARCH UNIT Gatty Marine Laboratory School of Environmental and Evolutionary Biology University of St Andrews Fife, Scotland KY16 8LB UK phone +44 (0)1334 462630 fax

Hello all, Does anyone know of any already written functions for carrying out stochastic dynamic programming in R? Thanks! Martin -- Martin Biuw Sea Mammal Research Unit Gatty Marine Laboratory, University of St Andrews St Andrews, Fife KY16 8PA Scotland Ph: +44-(0)1334-462637 Fax: +44-(0)1334-462632 Web: http://smub.st.and.ac.uk

Hello, I'm using the nls function and would like to increase the number of iterations. According to the documentation as well as other postings on R-help, I've tried to do this using the "control" argument: nls(y ~ SSfpl(x, A, B, xmid, scal), data=my.data, control=nls.control(maxiter=200)) but no matter how much I increase "maxiter", I get the following error

Hello, I've written a simple (although probably overly roundabout) function to test whether two regression slope coefficients from two linear models on independent data sets are significantly different. I'm a bit concerned, because when I test it on simulated data with different sample sizes and variances, the function seems to be extremely sensitive both of these. I am wondering if