similar to: Barplot and plot means with confidence intervals in the same plot

Hi all, I?m fitting GLM?s and I can?t interprete the coefficients when I run a model with interaction terms. When I run the simpliest model there is no problem: Model1<-glm (Fishes ~ Year + I(Year^2) + Kind.Geographic + Kind.Fishers + Zone.2 + Hours + Fishers + Month, family = poisson(log)) # Fishes, Year, Hours, and Fishers are numeric, Kind.Geographic, Kind.Fishers, Zone.2 and

*Hello all ** I am a newbie to R plotting maps. I am trying to plot over a world map a layer of Biogeochemical provinces (BGCP) by A.R. Longhurst. Each ocean region unfortunately are quite irregular in shape (not perfect squares). In GIS this layer of ocean provinces would be a layer of polygons, which I am assuming it cannot be plotted with R. I was wondering If anybody has encounter this

Hi all: I have a question about lm on t-test. data(sleep) I wanna perform t-test to test the difference between the 2 groups: I can use: t.test(extra~group) The t.test result shows that:t = -1.8608; mean1=0.75,mean2=2.33 But I still wanna use: summary(lm(extra~group)) Intercept=0.75,which is mean1,just the same as t.test. group2=1.58 means the difference of the 2 groups,so

I have a rather basic question. How can I get R to generate a ANOVA table and a f-value for a hypothesis test such as: Data: group1 values: 5.2 4.5 6.0 6.1 6.7 5.8 group2 values: 6.5 8.0 6.1 7.5 5.9 5.6 ... H0: mean1 = mean2 = mean3 = mean4 HA: at least two means different where I want to evaluate using a f test statistic? F = MSTr/MSE I'd like a table similar to one that

Dear all! After hours of trying around, I gave up: I have a 2-dimensional array, and I know how to split it into its rows and how to get the mean for every row using 'sapply'. But what I want is to calculate the mean over the first n rows, and then the second n rows, etc., so that I get a vector like: v == mean1(row 1:5), mean2(row6:10),... (trivial, you might say. I find it rather

Dear All I want to generate variable with Bivariate Normal Distribution by use mean1 = a, variance1 = b, mean2 = c, variance2 = d, rho = e. How I can do this. Many Thanks. IRD [[alternative HTML version deleted]]

Hi, I am a Ph.D. student from Québec, Canada. I’m a beginner with R and Bioconductor. Until now the only experience I have is in analyzing microarray data using affy and limma packages. Now I am trying to analyze Rat Gene 10 st arrays and I would like to run RMA analysis and Smyth moderated t test on those arrays. Since no cdf official package is available for those arrays, after reading many

Hello All, I posted a similar question before, but the direction was driven to whether my case is suitable for a wilcoxon test. After research about the appropriateness, I am pretty sure that a wilcoxon test is the right tool for my case. But how to compute the power of the test is still an unanswered question bothering me. The basic stats of my two paired samples are: mean1 = 0.0032, sd1 =

Hi, I am trying to write a function; I want to subtract the mean of each class in level 2 from the mean of each class in level 1 and square the answer, eg..... level.1 level.2 observation 1 1 0.5 1 1 0.2 1 2 0.6 1 2 0.4 2 3

Dear all, I found a discrepancy while performing a power calculation for a two sample t-test in R and S-PLUS, respectively. For given values of sample number (5 each), sd (0.2) , significance level (0.01), and a desired power (80%) I looked for the difference in means. These values differ: 0.5488882 in R and 0.4322771 in S-PLUS (see dump below). Did I overlook any detail or confuse some

Hi all, I am trying to run a linear mixed effect models in lmer() from the lme4 package using the weights option. I am using the R version 2.7.2 (2008-08-25) and lmer version in lme4_0.999375-26, which I think it is the latest version! I am getting and error message when I add the option "weights" in the lmer function. This is the error message I get "Error en

Hello, I am facing a problem with optimization in R from 2-3 weeks. I have some Gaussian mixtures parameters and I want to find the maximum in that *Parameters are in the form * mean1 mean2 mean3 sigma1 sigma2 sigma3 c1 c2 c3 506.8644 672.8448 829.902 61.02859 9.149168 74.84682 0.1241933 0.6329082 0.2428986 I have used optima and optimx to find the

Please help me in writing the R code for this problem. I've been solving this for 4 days. It was hard for me to solve it. It's a simulation problem in R. The problem is My true model is a normal mixture which is given as 0.5 N(-0.8,1) + 0.5 N(0.8,1). This model has two components. I will get a random sample of size 100 from this model. I will do this 300 times. That means, I will have

Dear Colleagues, does anybody know how to aggregate a data.frame using different functions for different columns? Sincerely ___________________ Markus Preisetanz Consultant Client Vela GmbH Albert-Roßhaupter-Str. 32 81369 München fon: +49 (0) 89 742 17-113 fax: +49 (0) 89 742 17-150 mailto:markus.preisetanz@clientvela.com

Un texte encapsul? et encod? dans un jeu de caract?res inconnu a ?t? nettoy?... Nom : non disponible URL : <https://stat.ethz.ch/pipermail/r-help/attachments/20101008/0bc9c0cc/attachment.pl>

Dear mailing list, For two normal distributions, e.g: r1 =rnorm(20,5.2,2.1) r2 =rnorm(20,4.2,1.1) plot(density(r2), col="blue") lines(density(r1), col="red") Is there a way in R to compute/estimate the point(s) x where the density of the two distributions cross (ie where x has equal probability of belonging to either of the two distributions)? Many Thanks Eleni

Dear list, Hello to everybody, I´m interested in finding a package for statistical analysis of binary data, I have a matrix with the following structure: Case1 Case2 Case 3 ....... CaseX Control1 Control2 Control3 ....... ControlY Pep1 1 0 1 1 0 0 0 1 Pep2 1 1 1 1 1 0 0 1 Pep3 0 1 1 1 1 0 0 1 ... Pepz 1 1 1 1 1 0 0 1 I would like to know some R package to calculte similarity matrix or

sorry for cross-posting Dear all, I have tow (several) bivariate distributions with a known mean and variance-covariance structure (hence a known density function) that I would like to compare in order to get an intersect that tells me something about "how different" these distributions are (as t-statistics for univariate distributions). In order to visualize what I mean hear a little

Hello r helpers! Below is the whole coding for my programme. Before proceed more further, let me explain for you. First of all, I need to compute trimmed mean. Till that step is ok. Then I need to compute ssdw which is sum of square deviation. If I do equal trimming at both tail of distribution that I chose, I will use the first ssd formulae which is "a". But if I am doing unequal

Hello, As a new user of R (less than a month) I have got my hands on several books and am pouting through the net looking for help in gaining understanding of this powerful tool. I am becoming more proficient with using basic functions to conduct basic statistics. I am now looking to learn how to write code. After a few small worthless functions I decided to try to create a function that was