[R] passing columns of tables as a variable to functions

hello! ive come across the following problem: im writing a function to ease the production of maps. as my tables have headers, id like to include an option in my function header to pass these columns to use them inside the evaluation block. the function looks as follows: # maptable #the name

[R] factorial map?

hello! i'm dealing with the following: i've collected a factor covariable at irregularly placed sampling points along a line with spatial informations, i.e.: dataset<-c(x-coordinates, y-coordinates, level-of-factor) the factor describes the density of vegetation between 0 (no ground cover) and

[R] interp function in package akima

hello! does anyone know how to get values out of an interp object (from akima package)? ive constructed an elevation map and would like to numerically see the calculated z values of data points, which were not empirically sampled (basically: id like to see the altitude at locations x,y which ha

[R] compare results of glms

dear list! i have run several glm analysises to estimate a mean rate of dung decay for independent trials. i would like to compare these results statistically but can't find any solution. the glm calls are: dung.glm1<-glm(STATE~DAYS, data=o_cov, family="binomial(link="logit")) dung.glm2<-glm(

[R] compare results of glms

dear list! i have run several glm analysises to estimate a mean rate of dung decay for independent trials. i would like to compare these results statistically but can't find any solution. the glm calls are: dung.glm1<-glm(STATE~DAYS, data=o_cov, family="binomial(link="logit")) dung.glm2<-glm(

[R] slightly off topic...

i'm sorry to bother but... sometimes theres an attachment in the posts on the list, a single file called: Teil 1.2 whys that? i dont want to open it to find out, as i have used computers before ;) therefore i suspect it to be either some security problem OR to be the alternative HTML version

[R] count data

hello dear list! I wonder about the layout of my csv for my study design: i have 11 different sites. each site had been visited 9 times. on each visit, 6 distinctive water parameters had been taken ONCE on each visit (as continuous variables). on each visit, the fish abundance was counted us

[R] accessing variables inside a function, inside a loop

dear list! I KNOW this has been answered a million times before. But, as some might remember from their "freelance" times as a statistic consultant, sometimes you're blinded by the facts. I KNOW I have seen this problem solved, but due to the mental blockade i have been suffering from the last

[R] png inside loop

hello list! I'm sorry, I just stumbled over this strange behaviour (at least I am not able to explain the behaviour, therefore I assume it to be a strange behaviour): attach(water) # I know, this is not recommended names(water[3:10]) [1] "temp" "pH" "DO" "BOD" "COD" "no3" "no2" "po4"

[R] general question about dropping terms of glm model fits

hello dear list! as I am currently helping someone with their statistical analysis of a count survey, I stumbled upon a very basic question upon model optimization: when fitting a model like: model<-lmer(abundance~(x+y+z)^3,family=poisson,...) in which x,y,z are continuous abiotic parameters

[R] pseudo-R by hand

hello dear list! since we want to do a model analysis and some people would like to see pseudo-R^2 values for different types of glm of a logistic regression, i've decided to write a function that computes either nagelkerkes normed pseudo-R or cox & snells pseudo-R. however, i am not clear as i

Re: [R] GLM and normality of predictors

Am 15.04.2011 20:14, schrieb Christian Hennig: Normality of the predictors doesn't belong to the assumptions of the GLM, so you don't have to check this. Note, however, that there are all kinds of potential problems which to detect is fairly hopeless with n=11 and three predictors, so you should

[R] Questionnaire Analysis virtually without continuous Variables

Hello! I am doing an analysis on a questionnaire of hunters taken in 4 different districts of some mysterious foreign country. The aim of the study was to gather info on the factors that determine the hunting success of a peculiarly beautiful bird in that area. All variables are factors, i.e.

[R] creating a contingency table from a data.frame automatically (NOT BY HAND)

Hello there! I am still struggling with a binomial response over all categorical variables (some of them with 3 levels, most with 2 levels). After initial struggles with glm's (struggle coming from the data, not the actual analysis) I have decided to prefer contingency tables. I have my data s