similar to: Documentation of model.frame() and get_all_vars()

Hello again, It appears that get_all_vars() incorrectly handles model formulae that use a right-hand side (rhs) matrix. For example, consider these two substantively identical models: # model using named variables mpg <- mtcars$mpg wt <- mtcars$wt hp <- mtcars$hp m1 <- lm(mpg ~ wt + hp) # model using matrix y <- mtcars$mpg x <- cbind(mtcars$wt, mtcars$hp) m2 <- lm(y ~ x)

Hi everyone, I've run into a bit of strange problem with implicit vs explicit printing and the call stack. I've included an example at the bottom of this email. The basic problem is that I have an S3 object with a print method. When the object is implicitly printed (ie. typed directly into the console) the function arguments in the call stack are exploded out to their actual values,

Dear all; I need to run heatmap. Because my first column in my data is alphanumeric, I can not run as.matrix(scale(my_data)). So I need to make my data readable as in data(mtcars). In *mtcars *data the first column is alphanumeric and has no name. Thanks, Greg [[alternative HTML version deleted]]

Dear List I have math test scores for male and female students where gender is a dummy code (female =1). I also have a variety of other demographic variables. However to begin, I want to create a very simple stripchart where female math scores are a blue circle and male scores are a red triangle. I am having difficulty using conditional statements to accomplish this. Thank you. ------

Before I go and do this another way - can I check if anyone has a way of looping through data in odfWeave (or possibly sweave) to do a repeating analysis on subsets of data? For simplicity lets use mtcars dataset in R to explain. Dataset looks like this: > mtcars mpg cyl disp hp drat wt ... Mazda RX4 21.0 6 160 110 3.90 2.62 ... Mazda RX4 Wag 21.0 6 160 110 3.90

On Thu, 1 Jun 2017, POLWART, Calum (COUNTY DURHAM AND DARLINGTON NHS FOUNDATION TRUST) via R-help wrote: > Before I go and do this another way - can I check if anyone has a way of > looping through data in odfWeave (or possibly sweave) to do a repeating > analysis on subsets of data? > > For simplicity lets use mtcars dataset in R to explain. Dataset looks like this: >

Full_Name: Liming Liang Version: 1.8.1 OS: windows2000 professional Submission from: (NULL) (67.172.81.139) I was looking at the variable 'mpg' of the data file 'mtcars' and make a stem plot, the following is the commend I entered. The stem plot shows the largest observation is 32.9 but actually in the data the largest observation is 33.9, here might be a problem. >

Dear list, I want the 1st, 2nd, 5th, and 6th columns of mtcars. After copying them, the columns become numeric class rather than data frame. But, when I copy rows, they data frame retains its class. Why is this? I don't see why copying rows vs columns is so different. > class(mtcars) [1] "data.frame" > head(mtcars) mpg cyl disp hp drat wt qsec vs

Typo: dat[[z]] should be x[[z]]: x2 <- do.call(rbind, lapply(names(x), function(z) data.frame(type=z, x[[z]]))) x2 type x y 1 A 1 3 2 A 2 4 3 B 5 7 4 B 6 8 David C -----Original Message----- From: R-help <r-help-bounces at r-project.org> On Behalf Of David L Carlson Sent: Wednesday, May 2, 2018 3:51 PM To: William Dunlap <wdunlap at tibco.com>; Kevin E.

Or add the type column first and then rbind: x <- list(A=data.frame(x=1:2, y=3:4),B=data.frame(x=5:6,y=7:8)) x2 <- do.call(rbind, lapply(names(x), function(z) data.frame(type=z, dat[[z]]))) ---------------------------------------- David L Carlson Department of Anthropology Texas A&M University College Station, TX 77843-4352 -----Original Message----- From: R-help

Hi, According to the help file for model.frame/get_all_vars, the following should produce the same output from both functions, but it doesn't... > dat <- list(X=matrix(1:15,5,3),z=26:30) > model.frame(~z+X,dat) z X.1 X.2 X.3 1 26 1 6 11 2 27 2 7 12 3 28 3 8 13 4 29 4 9 14 5 30 5 10 15 > get_all_vars(~z+X,dat) [1] z X <NA> <NA> <0

Dear R-help This is a follow-up to my previous post here: http://groups.google.com/group/r-help-archive/browse_thread/thread/d9b6f87ce06a9fb7/e9be30a4688f239c?lnk=gst&q=dobomode#e9be30a4688f239c I am working on developing an open-source automated system for running batch-regressions on very large datasets. In my previous post, I posed the question of obtaining VIF's from the output of

> get_all_vars(dist ~ speed, data = cars) Error in `row.names<-.data.frame`(`*tmp*`, value = c(NA, -50L)) : invalid 'row.names' length > version _ platform i386-pc-mingw32 arch i386 os mingw32 system i386, mingw32 status Under development (unstable) major 2 minor 5.0 year 2007 month

>>>>> Martin Maechler >>>>> on Mon, 18 Nov 2019 12:15:38 +0100 writes: >>>>> suharto anggono--- via R-devel >>>>> on Sun, 17 Nov 2019 10:34:31 +0000 writes: >> SVN revision 77401 changes >> x[isM] <- lapply(x[isM], function(o) `class<-`(o, class(o)[class(o) != "AsIs"])) >> to

SVN?revision?77401?changes ????????x[isM]?<-?lapply(x[isM],?function(o)?`class<-`(o,?class(o)[class(o)?!=?"AsIs"])) to ????????x[isM]?<-?lapply(x[isM],?function(o)?`class<-`(o,?class(o)[!inherits(o,"AsIs")])) in?function?'get_all_vars'?in?src/library/stats/R/models.R?in?R?devel. The?change?is?inappropriate.

Hi All, I am writing a function to predict values based on a model. It works fine as long as the formula just uses regular variable names. I am having a problem when the variables are wrapped with a function call. For example: m <- lm(mpg ~ factor(cyl), data = mtcars) ## I get the column names using as.character(attr(terms(m), "variables"))[-1L] ## which gives the same column

Dear R-Devel, I seem to no longer be able to access the bug-reporting system, so am doing this by e-mail. My report concerns models where variables are explicitly referenced (or is it "dereferenced"?), such as: cars.lm <- lm(mtcars[[1]] ~ factor(mtcars$cyl) + mtcars[["disp"]]) I have found that it is not possible to predict such models with new data. For example:

Dear all, What is the quickest and most efficient way to diff two data frames, so as to obtain a vector of indices (or logical) for rows/columns that differ in the two data frames? For example, > Xe <- head(mtcars) > Xf <- head(mtcars) > Xf[2:4,3:5] <- 55 > all.equal(Xe, Xf) [1] "Component 3: Mean relative difference: 0.6863118" [2] "Component 4: Mean relative

Sorry mistake from me. This was another problem in my mind , but with RMySQL. Christian > library(RMySQL) > library(sqldf) > sqldf("Select * from mtcars") Fehler in mysqlNewConnection(drv, ...) : RS-DBI driver: (Failed to connect to database: Error: Access denied for user 'user'@'localhost' (using password: NO) ) Fehler in if (dbname ==

class(o)[!inherits(o,"AsIs")] is still in function 'get_all_vars' in R patched (in https://svn.r-project.org/R/branches/R-3-6-branch/src/library/stats/R/models.R). It was ported to R patched by r77402. On Monday, 18 November 2019, 8:12:10 PM GMT+7, Martin Maechler <maechler at stat.math.ethz.ch> wrote: >>>>> Martin Maechler >>>>>? ?