similar to: lme problems

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

Hi! I have had this problem for a long time. I have tried to study the manuals and search the mailing lists, but I can not solve this. I think there has to be one simple solution to this, but I just can not find it. I have saved the data in excel (csv-format). Then I read the data in R e.g. >data <- read.csv2("example.csv", header=TRUE) I look the data and it looks ok. E.g

Hello, I have a statistical problem that I am using R for, but I am not making sense of the results. I am trying to use multiple regression to explore which variables (weather conditions) have the greater effect on a local atmospheric variable. The data is taken from a database that has 20391 data points (Z1). A simplified version of the data I'm looking at is given below, but I have a

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

Dear users, *******I have a function f to simulate data from a model (example below used only to show my problems) f<-function(n,mean1){ a<-matrix(rnorm(n, mean1 , sd = 1),ncol=5) b<-matrix(runif(n),ncol=5) data<-rbind(a,b) out<-data out} *********I want to simulate 1000 datasets (here only 5) so I use S<-list() for (i in 1:5){ S[[i]]<-f(n=10,mean1=0)} ******I have a

Hello, users. Dear users, *******I have a function f to simulate data from a model (example below used only to show my problems) f<-function(n,mean1){ a<-matrix(rnorm(n, mean1 , sd = 1),ncol=5) b<-matrix(runif(n),ncol=5) data<-rbind(a,b) out<-data out} *********I want to simulate 1000 datasets (here only 5) so I use S<-list() for (i in 1:5){ S[[i]]<-f(n=10,mean1=0)}

I want to obtain a barplot with error bars and a mean plot with error bars with other scale on the left in the same plot. I need help to get the same x axis (centered) when overlay two plots (barplot2 and plotCI (or lineplot.CI) with errorbars), with diferent y axis. I use par (new=T) but the X axis names are not centered with the figures. An example of my data:

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

Hello, Is it possible to draw level lines on the surface of a bivariate function? In the following example, to draw surface and levels lines for a multivariate normal law, I use persp, trans3d, contourLines and lines, but if the lines are correctly drawn, some parts of them are, of course, visible even if they are drawn on a non visible "face". Any suggestion to avoid this problem

Dear users, *******I have a function f to simulate data from a model (example below used only to show my problem) f<-function(n,mean1){ a<-matrix(rnorm(n, mean1 , sd = 1),ncol=5) b<-matrix(runif(n),ncol=5) data<-rbind(a,b) out<-data out} *********I want to simulate 1000 datasets (here only 5) so I use S<-list() for (i in 1:5){ S[[i]]<-f(n=10,mean1=0)} ******I have a very

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 =

SunOS fluke 5.8 Generic_108528-07 sun4u sparc SUNW,Ultra-Enterprise R-1.4.0 Running from the command line R CMD check chlib results in the log file 00check.log: * using log directory `/home/woodstock/hoffmann/R/Sources/chlib.Rcheck' * checking for file `chlib/DESCRIPTION' ... OK * checking package directory ... OK * checking for sufficient/correct file permissions ... WARNING *

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

I have many files (0.4.dat, 0.5.dat, ...) of which I would like to calculate mean value and variance and save the output in a new file where each line shouldlook like: "0.4 mean(0.4.dat) var(0.4.dat)" and so on. Right now I got a a simple script that makes me unhappy: 1. I run it by "R --no-save < script.r > out.dat" unfortunately out.dat has all the original commands in

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

SunOS fluke 5.8 Generic_108528-07 sun4u sparc SUNW,Ultra-Enterprise R-1.4.0 Running from the command line R CMD check chlib results in the log file 00check.log: * using log directory `/home/woodstock/hoffmann/R/Sources/chlib.Rcheck' * checking for file `chlib/DESCRIPTION' ... OK * checking package directory ... OK * checking for sufficient/correct file permissions ... WARNING *