similar to: Division of data frame and deletion of values from column

Hi all, I would like to remove rows from a matrix, based on the frequency of missing values. If there are more than 10 % missing values, the row should be deleted. I use the following to calculate the frequencies, thereby getting a new matrix with the frequencies: freqNA=rowMeans(is.na(exprdata)) But is there a shorter way to remove the rows based on "(1-freqNA)>0.1"

Here is the example. > age=18:29 > height=c(76.1,77,78.1,78.2,78.8,79.7,79.9,81.1,81.2,81.8,82.8,83.5) > type=c("A", "B", "C", "D","A", "B", "C", "D","A", "B", "C", "D") >

Hi all, Probably a simple question, but I just can't find a simple answear in the older threads or anywhere else. I've added some new vectors as columns in a data frame using cbind(). As they're all put as the last columns inte the data frame, I would like to move them to specific positions. How do you do to change the position of a column in a data frame? I know I can use

Hi all, I'm have a matrix (X) with observations as rows and parameters as columns. I'm trying to exchange all missing values in a column by the column mean using the code below, but so far, nothing happens with the NAs... Can anyone see where the problem is? N<-nrow(X) # Calculate number of rows = 108 p<-ncol(X) # Calculate number of columns = 88 # Replace by columnwise

Hi all, I need to replace missing values in a matrix by 10 % of the lowest available value in the matrix. I've got a function I've used earlier to replace negative values by the lowest value, in a data frame, but I'm not sure how to modify it... nonNeg = as.data.frame(apply(orig.df, 2, function(col) # Change negative values to a small value, close to zero { min.val =

Hi all, Does anyone know how to get the independent components and loadings from an Independent Component Analysis (ICA), as well as principal components and loadings from a Pricipal Component analysis (PCA) using the fastICA package? Or perhaps if there's another way to do ICAs in R? Below is an example from the fastICA manual (http://cran.r-project.org/web/packages/fastICA/fastICA.pdf)

Hi all, I'm searching for a way to exclude outliers from my dataset while making xyplots. While plotting using pairs(), I exclude specific row in my data frame and save the settings as a variable which I later include as an argument: # Discard outliers and save settings as idx idx=with(fieldTrial0809, which(Pro>0 & Pro<0.95 & Fum>0 & Fum<0.4 & Mal>0.1 &

Hi, I've got a data frame (556 rows and 36 columns) from which I need to create several xy plots and print to pdf, in order to detect outliers and trends in the data. 16 of the columns contains numerical values, and I would like to create graphs for all combinations. It can be done manually, but creating 256 plots by hand takes time... I guess I have to iterate through the data frame, but

Hi all, I'm doing Multiple linear regression for a data set. However, it takes a lot of time, as I would like to check every possible combination of factors, evalute the results based for instance on their p values, and then choose the best regression model. So, I wonder if anyone might have a script for that? Or if not, do you have some suggestions how to create such a script? I've

Hi all, I'm new to PCA in R, so this might be a basical thing, but I cannot find anything on the net about it. I need to make a PCA plot with two response variables (df$resp1 and df$resp2) against eight metabolites (df$met1, df$met2, ...) and I don't have a clue how to do... and I've only used the simplest PCAs before, like this: pcaObj=prcomp(t(df[idx, c(40:47)]))

Hi all, I'm making a PCA plot with eight variables (columns taken from a larger data frame "fieldTrial0809[idx,c(39:46)]"). I then want the symbols in the plot to be colored as a gradient from red to blue, depending on the value of another column in "fieldTrial0809[idx, c(48)]" containg temperatures from -12.1 to -5.4. I don't want to use the heat.colors(n)

Hi all, Anyone experienced in the LaTeX format? I'm trying to use the xtable package to create nice anova tables, but how do I do to produce a pdf from the resulting LaTeX table? I've tried WinShell and MiKTeX, but I couldn't get any of them working... Here's an example of the output in R: % latex table generated in R 2.9.2 by xtable 1.5-6 package % Tue Nov 24

Hi all, I've tried to make a 3D plot, but have run into some problems. I'd like to have a plot that I can rotate interactively using the mouse, which is possible using the plots3d {R.basic}. However, I would like to change the symbols used as the points, but there's no pch in plot3d(). If I use the Scatterplot3d package, I'm able to change this, but not able to rotate

Hello everybody, I'm using the lattice package and the xyplot to make several graphs like below. However, I can just print the three grouped plots onto one page as I'm putting them into a pdf-file, which gives me a huge amount of pages... Is it possible to put them all, or at least more than one on the same page, for instance put three groups beside each other like columns? ...

Hi all, I want to calculate the row wise mean of groups of columns in a matrix M. All columns belonging to the same group have the same column name. My idea is to create a new vector V containing these column names, but after first removing the duplicates. Then I would calculate the means using for instance rowMean() and by comparing the column names of M with the vector V, getting the indices

Hi all, I've got some problems when changing the trellis settings for the lattice plots. The plots look exactly as I want them to when calling show.settings() as well as when plotting them in the graphical window. But when printing to a pdf file, none of the settings are used!? Does anyone know what might have happened? Because the when changing the trellis settings, these should remain in

Hello, I would like to know if there is any package that allow us to fit Generalized Linear Models via Maximum Likelihood and Linear Models using Generalized Least Squarse in R as the functions glim and gls, respectively, from S-Plus. Also, anybody know if there is any package that fit Log-Linear Models using Generalized Least Squares? Any help will be very useful. Thanks, -- Frederico

Hello, I have the following data.frame structure(list(Study = structure(c(1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L,

hello, I'd like know how to sort a data frame in R for example how I should do to sort by Catholic with swiss data frame like below thanks Fertility Agriculture Examination Education Catholic Infant.Mortality Courtelary 80.2 17.0 15 12 9.96 22.2 Delemont 83.1 45.1 6 9 84.84 22.2

Hello, I am just installing XCP 0.1.1 on a server with 24GB RAM Normally XCP is a 64 bits version but * *uname -a* Linux node012 2.6.27.42-0.1.1.xs0.1.1.737.1065xen #1 SMP Fri Jan 15 16:20:16 EST 2010 i686 i686 i386 GNU/Linux (not a x86_64 version !!!!) * *cat /proc/meminfo* MemTotal: 746496 kB MemFree: 384332 kB Buffers: