similar to: How to sort data sets?

Hi, I was wondering if it is possible to get the rowindices without using the function "which" because I don't have a restriction criteria. Here's an example of what I mean: # take 10 randomly selected instances iris[sample(1:nrow(iris), 10),] # output Sepal.Length Sepal.Width Petal.Length Petal.Width Species 76 6.6 3.0 4.4 1.4

Dear all, I would like to use the values in vegaggr.BLMCMR02$colony str(vegaggr.BLMCMR02) `data.frame': 1678 obs. of 3 variables: $ vegtype : Factor w/ 27 levels "2010","2020",..: 3 4 5 19 4 5 19 5 $ colony : Factor w/ 406 levels "0","1","10","100",..: 1 1 1 1 2 2 2 $ Totvegproparea: num 0.00055 0.03956 0.95705

Hi, I am trying to use a vector of indices to select some rows from a matrix. But before I can do that I somehow need to convert 'combinations' into a list, since 'mode(combinations)' says it's 'numerical'. Any idea how I can do that? library("combinat") combinations <- t(combn(8,2)) indices <- c(sample(1:length(combinations),10)) # convert ???

Hi, all, Does anybody got the most general expression of a unitary matrix? I found one in the book, four entries of the matrix are: (cos\theta) exp(j\alpha); -(sin\theta)exp(j(\alpha-\Omega)); (sin\theta)exp(j(\beta+\Omega)); (cos\theta) exp(j\beta); where "j" is for complex. However, since for any two unitary matrices, their product should also be a unitary matrix. When I

Dear all, I have a population with three age-classes, at time t=0 the population is: n.zero <- c(1,0,0) I have a transition matrix A which denotes "fertility" and "survival": A <- matrix(c(0,1,5, 0.3,0,0, 0,0.5,0), ncol=3, byrow=TRUE) To obtain the population at t=1, I calculate: A %*% n.zero To obtain the population t=2, I calculate: A %*% (A %*% n.zero) ... and so

Hi, I am a user of R computer language.Several days ago,I download R-2.1.0.From the help manual,I saw there is a function "mle" to find the maximum likelihood estimators.But when I try to use this function,there is no this function.Could you help me to solve this problem? I am looking forward to your answer. Thank you. Jun Liu

Hey, I am estiamting a partially linear model y=X\beta+f(\theta) where the f(\theta) is estiamted using wavelets. Has anyone heard of methods to test if the betas are significant or to address model fit? Thanks for any thoughts or comments. Elizabeth Lawson __________________________________________________ [[alternative HTML version deleted]]

Hi, The question is as follows: has anyone coded panel data unit root tests with R? Even the "first generation" tests (see e.g. Levin & Lin 1993; Pesaran, & Smith & Im 1996; Maddala & Wu 1999) would be sufficient for my needs. To my understanding, these are rather easy to code, but as I have taken just my first steps in coding with R, existing code would save me

Dear R-users, Is anyone aware of any function/package for generating a random vector from a joint distribution defined by an independent graph? Or I have to work it out myself? Thanks. Jinfang ------------------------------ Jinfang Wang, Associate Professor Chiba University, Japan

This is what to start with: Data Frame A B C D c1 4 y 5 c3 6 d 7 c1 5 t 6 Now sort on A then C This is what to end with: Data Frame A B C D c1 5 t 6 c1 4 y 5 c3 6 d 7 I assume it is something like this: attach(DF) sort(DF,partial=c(A,C)) Thanks in advance. Meredith [[alternative HTML version deleted]]

Hi, I was wondering if it's possible to get the row numbers from a filtering. Here's an example: # give me the rows with sepal.length == 6.2 iris[(iris[,1]==6.2),] # output Sepal.Length Sepal.Width Petal.Length Petal.Width Species 69 6.2 2.2 4.5 1.5 versicolor 98 6.2 2.9 4.3 1.3 versicolor 127 6.2

I often use simple nested random-effect models for interlaboratory data. The variance components are important things to know. Is there an R function or package that gets variance components from lm objects? Or can someone point me to a method of doing so?

Hello and sorry to disturb. I'm trying to plot the confidence intervals for the fixed effects of a lme. I want to obtain graphically, if it is possible, a bar with Estimate, upper and lower CI for each level of the factors. I know how to do for a lm model but for a lme one, I tried with plot(intervals(...)) and plot(ci(...)) from the gmodels package but it doesn't work well. Thanks

Dear R users; Ive got two questions concerning nlme library 3.1-65 (running on R 2.2.0 / Win XP Pro). The first one is related to augPred function. Ive been working with a nonlinear mixed model with no problems so far. However, when the parameters of the model are specified in terms of some other covariates, say treatment (i.e. phi1~trt1+trt2, etc) the augPred function give me the following

Hi all, I encountered this problem with parameterization in R: I have two factors in a regression. how about if I want to set constraint so that for each factor, the sum of their coefficients equals to zero(instead of choosing a reference category)? for example, I have factor(variable) A(with three categories) and factor(variable) B(with 4 categories), and I want to parameterize so that the sum

Dear Friends, I am seeking for any help on an error message in lme functions. I use mixed model to analyze a data with compound symmetric correlation structure. But I get an error message: "Error in corMatrix.corCompSymm(object) : NA/NaN/Inf in foreign function call (arg 1)". If I change the correlation structure to corAR1, then no error. I have no clue how to solve this problem.

All, I've coded a function and it works manually if I copy it line by line into R. However, when I try to "load" (copy and paste) the entire function into R, I get the following error after the listed line of code: + N.j.list = lapply(rej.hyp, length) Error: symbol print-name too long Does anyone you know what this error means? Strangely, when I copy the same line verbatim

I'd like to be able to test linear hypotheses after setting up and running a model using optim or perhaps nlm. One hypothesis I need to test are that the average of several coefficients is less than zero, so I don't believe I can use the likelihood ratio test. I can't seem to find a provision anywhere for testing linear combinations of coefficients after max. likelihood. Cheers

Hello, I want to solve some two dimensional equation system with R. Some systems are not solvable analytically. Here is an example: (I) 1/n*sum{from_i=1_to_n}(Xi) = ln lambda + digamma(c) (II) mean(X) = x / lambda I want to find lambda and c, which R-function could do that task? Carsten [[alternative HTML version deleted]]

Hi using this code example: library(nlme) fm1 <- lme(Orthodont, random = ~1) plot(augPred(fm1)) is there any way to have the plots in each cell labelled and ordered according to Orthodont$Sex? I.e. in addition to the bar with the label for Orthodont$Subject there is another bar labelling the Sex of the subject? thanks a lot christoph --