similar to: Calculating "row standard deviations"

Hello, (1) what is the way to use table for the hole dataSet ? I would get a cross-table with x1 and other variables in the dataSet which have got 100 columns : table(x1,data[variable2 until variable 100])/length([variable2 until variable 100])*100 like this but it's wrong ? table(x1,data[,2:100])/length(data[,2:100])*100 if i type: table(data[,1:10]) to get the frequency

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

Greetings List, I'm having some trouble with the use of the names function in a formula. Below is an example of something that works (i.e first line), and the second line is the same formula which doesn't. I want to be able to reference the column of the dataC table so I can run the variogram iteratively with a loop. > v<-variogram(A1~1,loc=~x+y, dataC) >

Hi all, I am trying to fit t distribution using the function "tFit" in the library(fBasics). I am using the code tFit(datac[[2]]) and it returns the following list. Title: Student-t Parameter Estimation Call: tFit(x = datac[[2]]) Model: Student-t Distribution Estimated Parameter(s): df 78.4428 I just wonder how can I refer to the estimated parameters. I tried

Dear All- I am trying to merge two data files - they have different date formats and different times zones. I need to match up the date/time of the datasets and then invoke a conditional statement, such as: if dataC$mph is >= 12 then keep dataM$co23 for the corresponding time/date stamp. snippets of data files: *dataC.txt* LST in mph Deg DegF DegF2 % volts Deg

hello list, i'm a bit puzzled by the error message i get when i copy past this in R:

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

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:

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

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

Hi everyone, I have just started using R, and I have a simple question. How can I get the Standard deviation for rows. basically I am looking for something like "rowMeans()" but for Standard deviation (I tried "rowSds()" didn't exist) Thanks, -- View this message in context: http://www.nabble.com/Standard-deviation-for-rows-tp19998106p19998106.html Sent from the R

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]]

Hello! I have a dataset like this: X1 X2 X3 X4 X5 X6 X7 X8 1 2 2 1 2 3 2 6 2 3 2 5 7 9 1 3 1 9 12 6 1 1 3 6 The columns X1-X6 contains ordinary numeric values. X7 contains the number of the first column that the rowMeans should be calculated from and X8 contains the last column

> n=10;t=3 > d<-cbind(id=rep(1:n,each=t),y=rnorm(n*t),x=rnorm(n*t),z=rnorm(n*t)) > head(d) id y x z [1,] 1 -2.1725379 0.07629954 -0.3985258 [2,] 1 -1.2383038 -2.49667038 0.6966127 [3,] 1 -1.2642401 -0.50613307 0.4895856 [4,] 2 0.2171246 0.86711864 -0.6660036 [5,] 2 2.2765760 -0.48547142 -1.4496664 [6,] 2 0.5985345 -1.06427035 2.1761071

Hello all, I really appreciate how helpful the people in this list are. Would it be too much to ask to send a small script to have it peer-reviewed? to make sure I am not making blatant mistakes? The script takes an experiment.dat as input and generates system Throughput using ggplot2. It works now ... [sigh] but I have this nasty feeling that I might be doing something wrong :). Changing

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,

I would like to use the "row number" information returned from performing a subset command on a dataframe. For example, I would like to automatically delete some rows from a dataframe if they match a criteria. Here is my example below. data(airquality) names(airquality) subset(airquality, airquality$Month == 6) Now how do I delete the row numbers returned automatically? I

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 =