similar to: ggplot2 / reshape / Question on manipulating data

Hi All, If given a dataframe (long form) with Year, Species, and Location, How would I write a function that would create a unique matrix of Species & Location for each Year? What I've tried doing is the following: data #dataframe dataT<-table(data$Species,data$Location,data$Year) #creates tables of Species vs Location for each Year But I'm encountering issues individually

Dear list members, I recall seeing a convenience function for applying multiple functions to one object (i.e., almost the opposite of 'mapply?) somewhere. Example: If the function was named ?fun? the output of fun(3.14, mode, typeof, class) would be identical to the output of c(mode(3.14), typeof(3.14), class(3.14)) Is my memory failing me, or does such a function already exists in a

Are there any R functions for creating palettes for three-way data? For example, election maps for three parties where pure red, blue, and green show 100% for the Red, Blue, and Green parties respectively, magenta shows a 50-50 Red-Blue split with 0 for the Greens, cyan a 50-50 Blue/Green split with no Red votes and so on, with grey, black or white at a 1/3,1/3,1/3 split vote. I've spent a

Dear all, is there a convenient way to determine the effect size for a regression coefficient in a multiple regression model? I have a model of the form lm(y ~ A*B*C*D) and would like to determine Cohen's f2 (http://en.wikipedia.org/wiki/Effect_size) for each predictor without having to do it manually. Thanks, Michael Michael Haenlein Associate Professor of Marketing ESCP Europe Paris,

Hello, I have a log likelihood function that I was able to optimize using mle2. I have two years of the data used to fit the function and I would like to fit both years simultaneously to test if the model parameter estimates differ between years, using likelihood ratio tests and AIC. Can anyone give advice on how to do this? My likelihood functions are long so I'll use the tadpole

Dear R experts. I might be missing something obvious. I have been trying to fix this problem for some weeks. Please help. #data ped <- c(rep(1, 4), rep(2, 3), rep(3, 3)) y <- rnorm(10, 8, 2) # variable set 1 M1a <- sample (c(1, 2,3), 10, replace= T) M1b <- sample (c(1, 2,3), 10, replace= T) M1aP1 <- sample (c(1, 2,3), 10, replace= T) M1bP2 <- sample (c(1, 2,3), 10, replace= T)

Hello ! I am attempting to switch from being a long time SAS user to R, and would really appreciate a bit of help ! The first thing I do in getting a large dataset (thousands of obervations and hundreds of variables) is to run a SAS command PROC CONTENTS VARNUM command - this provides me a table with the name of each variable, its type and length; then I run a PROC MEANS - for numerical

Hi everyone I want help in graduating the attached rates and checking for goodness of fit and smoothness using R please help. Many thnk TOo every one around the world This message and attachments are subject to a disclaimer. Please refer to www.it.up.ac.za/documentation/governance/disclaimer/ for full details. / Hierdie boodskap en aanhangsels is aan 'n vrywaringsklousule onderhewig.