similar to: ANOVA f-test

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

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 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:

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

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 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 =

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

Dear all, I have weekly data by city (variable citycode). I would like to take the average of the previous two, three, four weeks (without the current week) of the variable called value. This is what I have tried to compute the average of the two previous weeks; df = df %>% mutate(value.lag1 = lag(value, n = 1)) %>% mutate(value .2.previous = rollapply(data = value.lag1,

Hi R-helpers, I have been struggling with calculating row and column statistics, e.g. standard deviation. I know that > datac$Mean<-rowMeans(datac,na.rm=TRUE) will give me row means. I have tried to replicate those row means with the apply function: > datac$Mean2<-apply(datac,2,mean) so that I can replace the function argument with "sd" (instead of mean) to get standard

Dear list, I'm currently trying to use the rms package to get predicted ordinal responses from a conditional ratio model. As you will see below, my model seems to fit well to the data, however, I'm having trouble getting predicted mean (or fitted) ordinal response values using the predict function. I have a feeling I'm missing something simple, however I haven't been able to

I have a bit of a quandy. I'm working with a data set for which I have sampled sites at a variety of dates. I want to use this data, and get a running average of the sampled values for the current and previous date. I originally thought something like ddply would be ideal for this, however, I cannot break up my data by date, and then apply a function that requires information

Hi, I am VERY interested in getting the xfig driver so that I can edit graphical output from R. Searching through the mail archives and reading documentation isn't helping. Is there or isn't there a working driver for this purpose. How can I get it? I tried looking at the development version of the tarballs, but I didn't find anything that looked promising in there. Also, does

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

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

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

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

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

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

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