similar to: quasi-random vector according to an independent graph

When I was computing some joint probabilities, I found that R reported most of the results to to -Inf and thus didn't record the value. I guess it is b/c the joint log(probability) can be extremely small. Is there a way in R to keep the values even if they are small?

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 --

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, 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

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

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]]

Dear All, I wonder if there is an efficient way to fit the generalized linear mixed model for multivariate outcomes. More specifically, Suppose that for a given subject i and at a given time j we observe a multivariate outcome Yij = (Y_ij1, Y_ij2, ..., Y_ijK). where Y_ijk is a binomial(n_ijk, p_ijk). One way to jointly model the data is to use the following specification: g(p_ijk) =

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

Hi, I am so novice in using R. I have some problems in my R script below which fits time series data and predict it one-step ahead. Here is a brief explanation on what I try to achieve Th16k is time series data (500 data points). The size of window for fitting and predicting is 50 (data points). As you can easily discover from my code, (fixed) window is moving/sliding to get next one-step

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

------------------------------------------------------------------------------------------------ CALL FOR PAPERS 15th International Conference on Managed Languages & Runtimes (ManLang'18) September 10-14, 2018, Linz, Austria http://ssw.jku.at/manlang18/ ------------------------------------------------------------------------------------------------ ManLang (formerly PPPJ) is a

GENERAL REFERENCE ON NONLINEAR OPTIMIZATION? What are your favorite references on nonlinear optimization? I like Bates and Watts (1988) Nonlinear Regression Analysis and Its Applications (Wiley), especially for its key insights regarding parameter effects vs. intrinsic curvature. Before I spent time and money on several of the refences cited on the help pages for "optim",