similar to: basic question re lm()

Hi all, Ive got a database with 10 columns (different variables) for 100 subjects, each column with different # of NA's. I'd like to know if it is possible to use a function to exclude the NA's using only a specific column, lets say: Data2 <- omit.exclude(Data1$column1) ??, then Data3 <- omit.exclude(Data1$column2) and so on I tried the code above but with no results Thanks

Hello to all is there a function wich splits a data.frame (column1,column2,column3,....) into data1 <-(column1,column3....) #column2 = 1 data2 <-(column1,column3....) #column2 = 2 data3 <-(column1,column3....) #column2 = 3 ... Regards Knut

Is there a way to get the following code to include NA values where the coefficients are ?NA?? ((summary(reg))$coefficients) explanation: Using a loop, I am running regressions on several ?subsets? of ?data1?. ?reg <- ( lm(lm(data1[,1] ~., data1[,2:l])) )? My regression has 10 independent variables, and I therefore expect 11 coefficients. After each regression, I wish to save the

I am using R 2.1.1 in an windows XP environment. I have 2 dataframes, temp1 and temp2. Each dataframe has 20 variables (“cocolumns") and 525 observations (“rows”). All variables are numeric. I want to create a new dataframe that also has 20 columns and 525 rows. The values in this dataframe should be the sum of the 2 other dataframe. (i.e. temp1$column

I have a dataset with 20 columns and ~600,000 rows. Column 1 has a number from 2-19. This number tells me, for each row, which column has the ?applicable? data. (i.e. the data that I wish to use for each individual row) I want to create a vector that contains the data from the value in column 1. e.g. If column 1, row 1, has a value of ?6?, I want to obtain the value in column 6, row1. If

Dear Lister, I understand merge() can be used to join 2 data frames based on 1 variable. But how about merge based on more than 2 variables? Thank you so much! -- WenSui Liu (http://spaces.msn.com/statcompute/blog) Senior Decision Support Analyst Health Policy and Clinical Effectiveness Cincinnati Children Hospital Medical Center [[alternative HTML version deleted]]

Hi all, I have a set of data in hourly time steps with each row identified as time data column1 data column2 1 9999 9999 1.042 9999 9999 1.083 9999 9999 1.125 9999 9999 1.167 9999

Hello, I've two data.frames (data1 and data4), dec="." and sep=";". http://r.789695.n4.nabble.com/file/n4199964/data1.txt data1.txt http://r.789695.n4.nabble.com/file/n4199964/data4.txt data4.txt When I do plot(data1$nx,data1$ny, col="red") points(data4$nx,data4$ny, col="blue") , results seem very similar (at least to me) but the R-squared of

I had a question about scan in R. For better code readability, I would like to have lines in the block of data to be scanned that are commented - not just lines that have a comment at the end. For example #age, weight, height 33,128,65 34,56,155 instead of having to do something like 33,128,65 #age, weight, height 34,56,155 Is this at all possible?

I'm trying to do a linear regression between the columns of matrices. In example below I want to regress column 1 of matrix xdat with column1 of ydat and do a separate regression between the column 2s of each matrix. But the output I get seems to give correct slopes but incorrect intercepts and another set of slopes with value NA. How do I do this correctly? I'm after the slope and

Hello Thomas, Consider that the primary bottleneck may be tied to memory usage and the complexity of pivoting extremely large datasets into wide formats with tens of thousands of unique values per column. Extremely large expansions of columns inherently stress both memory and CPU, and splitting into 110k separate data frames before pivoting and combining them again is likely causing resource

Hi Gregg. Just wanted to follow up on the solution you proposed. I had to make some adjustments to get exactly what I wanted, but it works, and takes about 15 minutes on our server configuration: temp <- ??????open_dataset( ????????????sources = input_files, ????????????format = 'csv', ????????????unify_schema = TRUE, ????????????col_types = schema( ????????????"ID_Key"

Hi Thomas, Glad to hear the suggestion helped, and that switching to a `data.table` approach reduced the processing time and memory overhead?15 minutes for one of the smaller datasets is certainly better! Sounds like the adjustments you devised, especially keeping the multicore approach for `make_clean_names()` and ensuring that `ID_Key` values remain intact, were the missing components you

is there a smart way of determining the number of pairwise present data in a data matrix with missings (maybe as a by-product of some statistical function?) so far, i used several loops like: for (column1 in 1:99) { for (column2 in 2:100) { for (row in 1:500) { if (!is.na(matrix[row,column1]) & !is.na(matrix[row,column2])) { pairs[col1,col2] <- pairs[col1,col2]+1

I am writing a custom function that uses an R-function from the reshape package: cast. However, my question could be applicable to any R function. Normally one writes the arguments directly into a function, e.g.: result=cast(table1, column1 + column2 + column3 ~ column4, mean) (1) I need to be able to write this statement as follows: result=cast(table1, string_with_columns ~

About to try this implementation. As a follow-up, this is the exact error: Lost warning messages Error: no more error handlers available (recursive errors?); invoking 'abort' restart Execution halted Error: cons memory exhausted (limit reached?) Error: cons memory exhausted (limit reached?) Error: cons memory exhausted (limit reached?) Error: cons memory exhausted (limit reached?)

I am new to R, but have been using SAS for years. In this transition period, I am finding myself pulling my hair out to do some of the simplest things. An example of this is that I need to generate a new variable based on the outcome of several existing variables in a data row. In other words, if the variable in all three existing columns are "Yes", then then the new variable should

Hi everyone, Hi want to separate the string(column1) for example column1 column2 column3 column4 column5 column6 bear b e a r cat c a t tiger t i g e r I know how to do this in excel where using MID function. Now I want to solve it using R. The list of strings is in

Hi all, We've just had a paper accepted for publication in Nature. We used R for 95% of our analyses (one of my co-authors sneaked in some GenStat when I wasn't looking.). The preprint is available from the Nature web site, in the open peer-review trial section. I searched Nature for previous references to "R Development Core Team", and I received no hits. So I tentatively

Hi, I have written boxplot commands of this form before, but I don''t quite understand why the function call is reporting a syntax error in this instance. All parameters passed to the function are strings. Thanks in advance. Payam > simplevar <- function(wframe,column1,column2) { + tframe <- get(wframe) + x1 <- which(names(wframe)==column1) + x2 <-