similar to: can't find "daphnia.txt" and others while working through Crawley's R-Book

Hello Everyone,   Learning about R and its wonderful array of functions. If it's not obvious, I usually try to find out what a function stands for. I think this helps me remember better.   One function that has me stumped is "sink." Can anyone tell me if this stands for something?   Thanks,   Paul         __________________________________________________ [[alternative HTML

Hi, I ran the example on pp. 799-800 from Machael Crawley's "The R Book" using package survival v. 2.36-5, R 2.13.0 and RStudio 0.94.83. The model is a Cox's Proportional Hazards model. The result was quite different compared to the R Book. I have compared my code to the code in the book but can not find any differences in the function call. My results are attached as well as a

Hi, I'm trying to set up R to run a simulation of two populations in which every 3.5 days, the initial value of one of the populations is reset to 1.5. I'm simulation an experiment we did in which we fed Daphnia populations twice a week with algae, so I want the initial value of the algal population to reset to 1.5 twice a week to simulate that feeding. I've use for loops and if/else

Hi, I have got to my hands an excellent book by Michael J. Crawley ``Statistical Computing: An Introduction to Data Analysis using S-Plus'' (John Wiley & Sons, Ltd, ISBN 0-471-56040-5). Its beauty for me is in the fact, that it is more of ``An Introduction to Data Analysis'' than ``using S-Plus'', but I guess that it may be of interest for many others. Most of the

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Hi, I try to run the example of Crawley's Book on the page 661, but it fail, look > repmeasures <- read.table("../Packages/Crawley/data/repmeasures.txt",header=T) > attach(repmeasures) > rep <- as.factor(rep) > library(nlme) > model <- lme(height~seed,random=~time|rep/seed) Erro em lme.formula(height ~ seed, random = ~time | rep/seed) : iteration limit

Hello all- I would appreciate any guidance that can be provided. I am new to R and am using it exclusively in a statistics program I am undertaking that mainly references Minitab. My focus is on data modeling and further more multivariate data analysis as much of my work in involves chemical measurements from custom sensors using all sorts of transduction methods. I am looking for a

Hello, I have consciously avoided using step() for model simplification in favour of manually updating the model by removing non-significant terms one at a time. I'm using The R Book by M.J. Crawley as a guide. It comes as no surprise that my analysis does proceed as smoothly as does Crawley's and being a beginner, I'm struggling with what to do next. I have a model: lm(y~A * B *

Hi, anybody have the dataset used in Gamma Errors chapter of the Crawley's books (An Introduction to Data Analysis using S-Plus). specifically the functionalresponse and the Density datasets. Thanks Ronaldo -- For every problem there is one solution which is simple, neat, and wrong. -- H. L. Mencken -- |> // | \\ [***********************************] | ( ? ? ) [Ronaldo Reis

Hi All, I would like to ask a question on fixed and random effecti in lme. I am fiddlying around Mick Crawley dataset "rats" : http://www.bio.ic.ac.uk/research/mjcraw/statcomp/data/ The advantage is that most work is already done in Crawley's book (page 361 onwards) so I can check what I am doing. I am tryg to reproduce the nested analysis on page 368:

I'm looking for a book for someone completely ignorant of statistics who wishes to learn both statistics and R. I've found three possibilities, one by Verzani ("Using R for Introductory Statistics"), one by Crawley ("Statistics: An Introduction using R"), and one by Dalgaard ("Introductory Statistics with R"). Do these books have different emphases,

Dear all, I am fitting a glm to count data using poison errors with the log link. My goal is to test for the significance of model terms by calling the anova function on two nested models following the recommendation in Michael Crawley's guide to Statistical Computing. Without going into too much detail, essentially, I have a small overdispersion problem (errors do not fit the poisson

Dear List, the advent of multicore machines in the consumer segment makes me wonder whether it would, at least in principle, be possible to divide a computational task into more slave R processes running on the different cores of the same processor, more or less in the way package SNOW would do on a cluster. I am thinking of simple 'embarassingly parallel' problems, just like inverting

Hi All: Read Ralf Karrenberg's excellent 'packetizing paper - a component of AnySL. I'm interested in working with something just like this as an alternative to traditional vectorization with 'embarassingly' parallel workloads. Anyone know if there is a release of Ralf's or similar work? -Matt -------------- next part -------------- An HTML attachment was scrubbed...

Dear friends, I am testing glm as at page 514/515 of THE R BOOK by M.Crawley, that is on proportion data. I use glm(y~x1+,family=binomial) y is a proportion in (0,1), and x is a real number. I get the error: In eval(expr, envir, enclos) : non-integer #successes in a binomial glm! But that is exactly what was suggested in the book, where there is no mention of a similar warning. Where am I

New installation seems to have behavior I cannot figure out. Here is illustrative sequence where I load a small data set (test) from Crawley's files and try to run a simple linear model and get an error message. Oddly, R reports that the variable 'test$ozone' is numeric while, after attaching test, the variable ozone is not numeric. Can someone please help? This behavior is

I handle SysAdmin for a multi-user Linux box, with R 2.7.1 compiled and installed to make usee of ACML (Opteron chips). The library files (packages) are installed to /usr/local/lib64/R/library Everything works as it should, except for the following. Say I have a user (an R developer) who has developed a package called Blaster. We'll call the user guru. Now, /home/guru/Blaster, contains the

I'm trying to learn statistics and R at the same time. I have an undergraduate science degree and one year of calculus (30 years ago), but never took a stats course. I hope to take some stats courses in the next year, but thought I would start to see how much I could teach myself. I work for an organization that analyses behavior change communication programs regarding HIV/AIDS and

Apologies if this has been asked before. I am having trouble understanding the R mailing list never mind R! I am relatively new to R having migrated from Minitab and SPSS. I have managed to do some more complicated statistics such as hierarchical partitioning of variance on an 80,000 record dataset but have to admit that drawing a simple bar plot I could do by hand is proving extremely

Dear R people, I wonder if you could give me a hand with some of my data. I have a very typical analysis in biology, however it is difficult for me to find the right way to analyse. I had a group of animals, I gave them a treatment, and I measure a variable along time -one??s per day- along 5 days,for example(fake data): Animals Time1 Time2 Time3 Time4 1 1 5 3