similar to: Column renaming

Hello, I would like to create a subscriptable collection (presumably a list) of lm() models. I have a data frame DX containing 6 groups of data. The general idea is (NOT RUN) ... for (i in 1:6) { DXS = subset( DX, <whatever>); LMX[ i] = lm( <formula>, data = DXS); } Now access model results by subscript ... e.g. coefficients( LMX[ 2]). Or would it be [[ 2]]? I

Greetings, Q #1 ------ How does one combine data frames by row ... no cleverness a la merge(), just add rows. For example, given A with 20 rows and B with 30 rows, I want C = combine( A, B) having 50 rows. Columns having matching names should be filled from both (all) sources with suitable coercion, unmatched would get NA in rows whose source does not have that column. Q #2 ------ Given

Dear all -- I have a data frame containing data related to heat gain through windows. The general form is ... Key ProfA IAC <many other numeric columns> AAA 0 .7 AAA 10 .6 AAA 0 .66 AAA 20 .45 (more AAA rows) (then AAB rows) 'Key' identifies the physical configuration ... rows with a given Key contain data for same window under various

Dear all -- I want to compute weighted.mean() for grouped rows. Data frame extract is just below. For each Key, I want the mean of IAC weighted by Wt. DP0[1:20,] Key IAC Wt 2 C3-PD030020050.PD030020050.3.12.3.0 0.765 0.8590000 3 C3-PD030020050.PD030020050.3.12.3.0 0.764 0.8449651 4 C3-PD030020050.PD030020050.3.12.3.0

Dear R-ers, My aggregation saga continues. Using the following sequence, I can calculate any statistic for row groups and merge the result back to all associated rows ... > WM = by( D60, D60[ "KeyProfA"], FUN=function(x) weighted.mean( x$IAC, x$Wt)) > D60$IAC.WM = as.numeric( WM[ D60$KeyProfA]) > class( WM) [1] "by" Questions ... 1) Is this a reasonable way

Dear R-people ... I'm a new user. I can't get predict.lm() to produce predictions for new independent data. There are some messages in archived help about this problem, but I still don't see my error after reviewing those. I understand that the new independent data must have the same name(s) as used when the model was made. In the example below, predict.lm produces the

Is there a limit to the number of columns that a data.frame can have? For example, can I read.csv() a file that has 1000 columns and 10,000 rows, will it break or is it limited by available memory. ................................................................................... Philip Sobolik 781-862-8719 x111 Wrightsoft Corporation 781-861-2058 fax 394 Lowell

The behaviour of within() with list input changes if you delete 2 or more variables, compared to deleting one: l <- list(x=1, y=2, z=3) within(l, { rm(z) }) #$x #[1] 1 # #$y #[1] 2 within(l, { rm(y) rm(z) }) #$x #[1] 1 # #$y #NULL # #$z #NULL When 2 or more variables are deleted, the list entries are instead set to NULL. Is this intended?

I would like to add a column to the airquality dataset that contains the date 1950-01-01 in each row. This method does not appear to work: > attach(airquality) > data1 <- transform(airquality,Date=as.Date("1950-01-01")) Error in data.frame(list(Ozone = c(41L, 36L, 12L, 18L, NA, 28L, 23L, 19L, : arguments imply differing number of rows: 153, 1 I can't decipher what

My apologies in advance for my thickness but I can't seem to solve the following, seemingly simple, data manipulation problem: I have a data frame that contains multiple factors and multiple continuous response variables, but duplicates of some factor combinations. The duplicates contain bad data, so I would like to eliminate the duplicates. I would like to retain the entire rows

>>>>> peter dalgaard <pdalgd at gmail.com> >>>>> on Mon, 26 Jun 2017 13:43:28 +0200 writes: > This seems to be due to changes made by Martin Maechler in > 2008. Presumably this fixed something, but it escapes my > memory. Yes: The change set (svn -c46441) also contains the following NEWS entry BUG FIXES o

Hi, all I have a question on mgcv and ns. Now I want to compare the results from glm, gam and ns. Take a simple model y~x for example. glm1 = glm(y~x, data=data1) gam1 = gam(y~s(x), data=data1) ns1 = glm(y~ns(x),data=data1) In order to confirm the result from glm1 is consistent to those from gam1 and ns1, I want to define degree=1 in mgcv and ns. I am wondering if there is somebody can give me

Hi all. 1) If I have a dataframe with variable names as follow: PC1 PC2 ... PCn and I want to pass only some of them to a function, e.g. glm(resp~from PC1 to PC10, PC15, etc.,...) is there a faster way than simply writing each variable name in the formula? 2) Again, I have a dataframe, say ali.df, with tha following variables: ali1, ali2, ...ali78 I want to sum, for example, ali1+al2+ali7+f rom

Hello Given the following data for a data set called airquality. To identify the nature of the objects from the data set airquality example "Ozone" would it be best to use the command is. like is.character(airquality$Ozone) ....... I tried attributes(airquality$Ozone) but it came up null. Would there be a better way to identify these objects. Thanking you in advance for your

Hi All, I've reproduced the example from Prof. Friedrich Leisch's webpage. When I write sweave("Example-1.Snw") OR sweave("Example-1.Rnw"), (yes, I renamed them). I get the following error: Writing to file example-1.tex Processing code chunks ... 1 : echo term verbatim Error: chunk 1 Error in library(ctest) : there is no package called 'ctest' Also while

Hello, I am running randomForest models on a number of species. I would like to be able to automate the printing of dependence plots for the most important variables in each model, but I am unable to figure out how to enter the variable names into my code. I had originally thought to extract them from the $importance matrix after sorting by metric (e.g. %IncMSE), but the importance matrix is n

I think I've gotten my Emacs/Sweave/R system set up correctly, thanks to Vincent and Jim, but I haven't been successful getting my first document produced. I'm trying to use one of Friedrich Leisch's examples, http://www.ci.tuwien.ac.at/~leisch/Sweave/example-1.Snw. I cut and pasted the text into a document sweaveexample.Rnw in Emacs. It seemed to be processed successfully with R:

Hi all, I am reading books and tutorials about R. I don't understand the following: plot(salary~rank, data=salary) plot(Ozone~date, data=airquality) I don't understand what does "~" here, and how can plot() have a input argument called "data"... I have looked it up in "plot"'s help but I could not find about argument "data". Could you please

Dear R list, members of my course have encountered the following error message: > slm <- lm(price ~ engsize, autoframe) Error in get(x, envir, mode, inherits) : variable "FUN" was not found [more context is given in the fuller listing below]. Once the error is encountered it seems to persist; for example early in one session: > summary(blin.fit) Call: lm(formula = Response

> library(reshape2) > x = melt(airquality, id=c('month', 'day')) With reshape I can cast with multiple functions: > library(reshape) > cast(x, month+variable~., c(mean,sd)) month variable mean sd 1 5 ozone 23.615385 22.224449 2 5 solar.r 181.296296 115.075499 3 5 wind 11.622581 3.531450 4 5 temp 65.548387