similar to: ANCOVA method

Dear R-helpers, In my dataset I have two continuous variable (A and B) and one factor. I'm investigating the regression between the two variables usign the command lm(A ~ B, ...) but now I want to know the regression coefficient (r2) of A vs. B for every factors. I know that I can obtain this information with excel, but the factor have 68 levels...maybe [r] have a useful command. Thanks,

Dear R-users, I have to plot two xyplot, and I wish to enclose this two graphs with just one headline, the same x scale, the same grid etc. These parameters should tie in, in order to obtain, visually, a unique graph formed by two xyplot. I try to give an idea: xyplot1: |_|_|_| xyplot2: |_|_|_| what i want: | | | | |_|_|_| I tried to use the command

Dear R-users, I need to produce a histogram where for every breaks there are the mean of the data. I tried tu use the function >hist(x, break=20 ... ) but this return the numerosity for every breaks, not the mean. Any hint? Thanks in advance, francesco --------------------------------------- Francesco Nutini CNR-IREA Ist. per il Rilevamento Elettromagnetico dell'Ambiente Via

Dear R-Users, I'd like to have some tips about printing graph. I use the command par to print more graphs in one window:par(mfrow=c(6,1)); par(oma=c(2.5, 2.5, 2.5, 2.5)); par(mar=c(0.5,4, 0.5, 0.5)) But this command doesn't run with complex graphic command (i.e. xyplot, ternaryplot).How can I print more than one graph per page, when I work with this "elaborated" graph?Many

Dear R users, I'm using xyplot to obtain a graph about a correlation x~y for different years (a categoric variable). The program dispose automatically the graphs in this way: 2010 2007 2008 2009 2004 2005 2006 2001 2002 2003 1998 1999 2000 Which code should I use to obtain this sequance of graphs? 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 I have tried with

Dear R-Users, I'd like to have your help on this problem: I have two vectors:x<- c(0,1,0,0,0,0,0,0,0,0,0,1,0)y<- c(0,0,-10,0,0,-10,0,-10,0,0,0,0,0) And I want to know where the value -500 in y have a correspondence value 1 in x.Considering a buffer of one position before and after in x.i.e. in this example only the -10 in position y[3] satisfies the criteria, because x has in position

Dear R-users, I'm studing a DB, structured like this (just a little part of my dataset): _____________________________________________________________________________________________________________ Site Latitude Longitude Year Tot-Prod Total_Density dmp Dendoudi-1 15.441964 -13.540179 2005 3271.16 1007 16993.25 Dendoudi-2 15.397321 -13.611607

Dear R-Users, I'd like to have some tips for a ternaryplot ("vcd"). I have this dataframe: a<- c (0.1, 0.5, 0.5, 0.6, 0.2, 0, 0, 0.004166667, 0.45) b<- c (0.75,0.5,0,0.1,0.2,0.951612903,0.918103448,0.7875,0.45) c<- c (0.15,0,0.5,0.3,0.6,0.048387097,0.081896552,0.208333333,0.1) d<- c (500,2324.90,2551.44,1244.50, 551.22,-644.20,-377.17,-100, 2493.04)

Dear Members, Greetings! I have come across a discrepancy shown by R and SAS results on same data for logistics regression.. When I processed the above csv file(1000.csv) for predicting the Action (i/c) by Age Group(1-7,Na) and Gender(M,F,Na) with GLM of R I get: R result Call: glm(formula = Action ~ Gender + AgeGroup, family = binomial, data = mydata1, na.action = na.pass) Deviance

Dear Alex, I have read your question about post-hoc test: "Let's assume that according to Anova(lm(y~a*b, data=d)) the a:b interaction is significant, and I would like to know if there are specific combinations of a and b levels that differ from the control group. Are there any caveats against simply looking at the p-values in the output generated by summary(lm(y~a*b,data=d))? The

R friends, In a matrix of 1s and 0s, I'm getting a singularity error. Any helpful ideas? lm(formula = activity ~ metaF + metaCl + metaBr + metaI + metaMe + paraF + paraCl + paraBr + paraI + paraMe) Residuals: Min 1Q Median 3Q Max -4.573e-01 -7.884e-02 3.469e-17 6.616e-02 2.427e-01 Coefficients: (1 not defined because of singularities)

Hi. I am using the Matching package for propensity score matching. For each treated unit, I want to find all control units whose propensity scores lie within a certain distance from the treated unit. The sample code is as follows: > library(Matching) > x <- rnorm(100000) > y <- rnorm(100000) > z <- rbinom(100000,1,0.002) > logit.reg <-

Dear Rusers, I have met a difficult problem on explaining the differences of principal component analysis(PCA) between R,S-PLUS and SAS/STATA/SPSS, which wasn't met before. Althought they have got the same eigenvalues, their coeffiecients were different. First, I list my results from R,S-PLUS and SAS/STATA/SPSS, and then show the original dataset, hoping sb. to try and explain it.

Hi, if i have data in the following time series format: time, amount, state 1 2222 A 1 333 B 2 45 A 2 77 B where states could be n and time periods t is there a package in R that would calculate the transition probabilities in a markov chain. for each t except t=0 to generate A B A B perhaps the best structure might

Target: FreeBSD 6.2-STABLE on i386 autoconf says: configure:2122: checking build system type configure:2140: result: i386-unknown-freebsd6.2 [...] configure:2721: gcc -v >&5 Using built-in specs. Configured with: FreeBSD/i386 system compiler Thread model: posix gcc version 3.4.6 [FreeBSD] 20060305 [...] objdir != srcdir, for both llvm and gcc. Release build. llvm-gcc 4.2 from source.

Hi I think I have asked these questions earlier, but I been able to find answers from the documentation (which I found poorly written in several places). Will someone be kind enough to give me answers and enlighten me? (as in explain with CODE?) I want to embed R in my application and use the fPortfolio package for carrying out risk management computations. Right now I'm reading the Rmetrics

LLVMers, The 2.2 prerelease is now available for testing: http://llvm.org/prereleases/2.2/ If anyone can help test this release, I ask that you do the following: 1) Build llvm and llvm-gcc (or use a binary). You may build release (default) or debug. You may pick llvm-gcc-4.0, llvm-gcc-4.2, or both. 2) Run 'make check'. 3) In llvm-test, run 'make TEST=nightly report'. 4) When