similar to: mfrow and centering plots when there's an odd number

Hi all- I fit a zero-inflated Poisson model to model bycatch rates using an offset term for effort. I need to apply the fitted model to a datasets of varying levels of effort to predict the associated levels of bycatch. I am seeking assistance as to the correct way to code this. Thanks in advance! Laura [[alternative HTML version deleted]]

R users doing data analysis may be interested in the following paper: http://methodsblog.wordpress.com/2009/11/13/first-paper-now-online/?utm_source=feedburner&utm_medium=feed&utm_campaign=Feed%3A+wordpress%2Fmethodsblog+(methods.blog) All data and R code is available. Alain ----- -------------------------------------------------------------------- Dr. Alain F. Zuur First author of:

Hello, I am using R to analyze a large multilevel data set, using lmer() to model my data, and using anova() to compare the fit of various models. When I run two models, the output of each model is generated correctly as far as I can tell (e.g. summary(f1) and summary(f2) for the multilevel model output look perfectly reasonable), and in this case (see below) predictor.1 explains vastly more

Dear All, the lm() function has the possibility to create a subset of the possible explaining variables that you have. However, in the help there is no example how to use this subset option. I tried the following: model<-lm(dependent.data$MPFD~.,data=explaining.data,subset=c(1,0,0,0,0,0,0,0,1,1,0,0)) MPFD is the dependent variable stored in the data frame dependent.data, and all 12

Dear all, I'm a beginner of R and I need to carry out some three-way mixed ANOVAs. Following examples at http://personality-project.org/r/r.anova.html, I managed to get the ANOVA part, but I don't know how can I check data normality and homogeneity of variance in R (since they're the required assumptions of ANOVA analysis). Are there any special command/packages? Could anyone give me

Hi, I am trying to add multiple variance structures such as the first example below: vf1 <- varComb(varIdent(form = ~1|Sex), varPower()) However my code below will not work can anybody please advise me? VFcomb<-varComb(varExp(form=~depcptwithextybf),varFixed(form=~FebNAO)) also if you have two variables with the same weights function would you write that as:

Hi, All, I have a dataset with binary response ( 0 and 1) and some numerical covariates. I know I can use logistic regression to fit the data. But I want to consider more locally. So I am wondering how can I fit the data with 'loess' function in R? And what will be the response: 0/1 or the probability in either group like in logistic regression? Thank you, Cindy [[alternative HTML

Hi - I read through dse package manual a bit. I'm not quite certain how I can use it to estimate a time varying coefficient regression model? I might pick up an inappropriate package. Any suggestion would be greatly appreciated. Thank you. rh

Dear Group, I am an economics student starting with PhD work in London. As preparation I would like to get to know R a little bit better. For Stata there are tons of books, however, can you recommend a book for R? I have some substantiated econometrics knowledge, so it should be more a how-to book. Best regards Thiemo --- Thiemo Fetzer, Economist http://freigeist.devmag.net

Hello, I'm having an error when trying to fit the next GLM: >>model<-glm(response ~ CLONE_M + CLONE_F + HATCHING +(CLONE_M*CLONE_F) + (CLONE_M*HATCHING) + (CLONE_F*HATCHING) + (CLONE_M*CLONE_F*HATCHING), family=quasipoisson) >> anova(model, test="Chi") >Error in if (dispersion == 1) Inf else object$df.residual : missing value where TRUE/FALSE needed If I fit

Dear R-helpers, I would like to compare the fit of two models, one of which I fit using lm() and the other using glm(family=poisson). The latter doesn't provide r-squared, so I wonder how to go about comparing these models (they have the same formula). Thanks very much, Mark Na [[alternative HTML version deleted]]

Hi, I wrote a simple master function, run(), that has inside six qplot functions. The goal is to type run() and have all six graphs appear as separate windows so that I can copy them into PowerPoint for a client. When I type run(), only the last graph appears, the first five apparently being overwritten. How do I get all six in separate windows, ready for copying? By the way, is the a way

Hi while teaching R, the question came up if it would be possible to add a picture (saved on the HDD) to a graph (generated by plot()), which we could not answer. It might easily kill a clean graph, but: is there a way of doing this, even one should not do it? On a similar line of thought: is it possibe to define own symbols so that they can be used in the plot function with pch=? Rainer

Hi everyone! I'm new to R, and I've sent this message as a non-member, but since it's pretty urgent, I'm sending it again now I'm on the mailing list (Thanks Daniel for your suggestion nevertheless). I have calculated a regression in the form of M ~ D + O + S, and I would like to take this regression and test it with other samples, 5 sets of M, D, O, and S at a time(I actually

We would like to announce the following statistics course: Introduction to zero inflated models and GLMM 13 - 16 May 2013. Elche, Spain. For details, see: http://www.highstat.com/statscourse.htm Course flyer: http://www.highstat.com/Courses/Flyer2013_05Elche_ZIP.pdf Kind regards, Alain Zuur -- Dr. Alain F. Zuur First author of: 1. Analysing Ecological Data (2007). Zuur, AF, Ieno, EN and

Dear R Community, I?m relatively new in the field of R and I hope someone of you can help me to solve my nerv-racking problem. For my Master thesis I collected some behavioral data of fish using acoustic telemetry. The aim of the study is to compare two different groups of fish (coded as 0 and 1 which should be the dependent variable) based on their swimming activity, habitat choice, etc.

Members of this mailing list may be interested in the following new book: Beginner's Guide to GLM and GLMM with R. - A frequentist and Bayesian perspective for ecologists - Zuur AF, Hilbe JM and Ieno EN This book is only available from: http://www.highstat.com/BGGLM.htm This book presents Generalized Linear Models (GLM) and Generalized Linear Mixed Models (GLMM) based on both

Hello everyone I have some data of the following type. 100 200 300 400 500 1.1 1.2 1.3 1.4 1.5 600 700 800 900 1000 1.5 1.7 1.9 2.0 2.4 With plot() and points functions I can plot these 4 lines of data. But I dont know how to do it with qplot or ggplot functions. The scenario is something like this: the hundreds should appear on x-axis and the fractional values of y axis. Thanks alot. MEMON

There are 8 remaining seats on the following course: Introduction to linear mixed effects modelling and GLMM course. Where: Banff, Canada When: 27-31 May, 2013 For details see the flyer at: http://www.highstat.com/Courses/FlyerCanada2013.pdf or: http://www.highstat.com/statscourse.htm Kind regards, Alain Zuur -- Dr. Alain F. Zuur First author of: 1. Analysing Ecological Data (2007).