similar to: Unused argument "na.action" to pairs.formula

Dear all, I would like to suggest changing the pairs.formula command such that a command like pairs(GNP ~ . - Year - GNP.deflator, longley) would behave in a similar fashion as lm(GNP ~ . - Year - GNP.deflator, longley) i.e., make a pairwise scatterplot of GNP and all other variables in the (longley) dataframe except for Year and GNP.deflator. The above command, with the

(RFC := Request For Comments) >>>>> "Tim" == Tim Keighley <Tim.Keighley@csiro.au> >>>>> on Thu, 23 Oct 2003 11:45:22 +1000 writes: Tim> Hi Martin, Tim> In October 2000 you wrote to r-help: >>> which reminds me that I've had a desire for something like >>> the old S function [from the blue book, and

Hi, When writing formulae in Rd files I use \leq to get a less-than-or-equal-to sign, as this is what the LaTeX references I consulted suggested. This works correctly for the PDF output (Rcmd Rd2dvi.sh --pdf), however when the Rd file is converted to text or html this command is converted to "<=q". A workaround is to use \le instead of \leq which works with my LaTeX distribution

Sorry for posting this twice, but I still have not solved this problem and am hoping for some assistance. I am attempting to write a function that is flexible enough to respond to the user providing a formula (with a data= argument) or not (similar to plot(x,y) versus plot(y~x,data=data)). I have found a method to work with this in a simple case but am having trouble determining how to

I could use some help understanding how nls parses the formula argument to a model.frame and estimates the model. I am trying to utilize the functionality of the nls formula argument to modify garchFit() to handle other variables in the mean equation besides just an arma(u,v) specification. My nonlinear model is y<-nls(t~a*sin(w*2*pi/365*id+p)+b*id+int,data=t1,

Dear all, Using the tsls package, I noticed that regression lists longer than 64 character are getting truncated. Looking at the original source, tsls.formula <- function(model, instruments, data, subset, weights, na.action, contrasts=NULL){ if (missing(na.action)) na.action <- options()$na.action m <- match.call(expand.dots = FALSE) if (is.matrix(eval(m$data,

I could use some help understanding how nls parses the formula argument to a model.frame and estimates the model. I am trying to utilize the functionality of the nls formula argument to modify garchFit() to handle other variables in the mean equation besides just an arma(u,v) specification. My nonlinear model is y<-nls(t~a*sin(w*2*pi/365*id+p)+b*id+int,data=t1,

I could use some help understanding how nls parses the formula argument to a model.frame and estimates the model. I am trying to utilize the functionality of the nls formula argument to modify garchFit() to handle other variables in the mean equation besides just an arma(u,v) specification. My nonlinear model is y<-nls(t~a*sin(w*2*pi/365*id+p)+b*id+int,data=t1,

I'm trying to write a formula method for canonical correlation analysis, that could be called similarly to lm() for a multivariate response: cancor(cbind(y1,y2,y3) ~ x1+x2+x3+x4, data=, ...) or perhaps more naturally, cancor(cbind(y1,y2,y3) ~ cbind(x1,x2,x3,x4), data=, ...) I've adapted the code from lm() to my case, but in this situation, it doesn't make sense to include an

Full_Name: Steven McKinney Version: R 2.8.0 Patched svn rev 46845 OS: powerpc-apple-darwin9.5.0 Submission from: (NULL) (142.103.207.10) <<insert bug report here>> lines.formula() throws an error when subset argument is used but nothing is provided for data argument. Reproduce: x<-1:5 y<-c(1,3,NA,2,5) plot(y~x, type="n") # set up frame lines(y~x,

Peter, There is a clear and simple bug in glm() that I have noticed in 0.64.2 (Windows and Unix) but may have been present in earlier versions. The function starts as follows: > glm function (formula, family = gaussian, data = list(), weights = NULL, subset = NULL, na.action = na.fail, start = NULL, offset = NULL, control = glm.control(...), model = TRUE, method =

Dear List The UKgas data is stored as an object of class 'ts'. I am trying to use "UKgas" in a formula as argument to a function. However, I do not know how to access the 'time series' information in the response (such as start() end() etc.). Here is a boiled down example. ssm <- function(formula, data = list(),subset=NULL) { cl <- match.call() if

I'm trying to create a formula object to pass on to a function that applies the function terms.formula() to it. f <- function(formula, ...) { ... mf <- match.call() term <- terms.formula(mf$formula) ... } However, my code below gives an error. form <- as.formula("y~x") f(form, ...) The error message was: Error in terms.formula(mf$formula): argument is not a valid

Dear all, I noticed the following bug in points.formula > library(DAAG) > data(roller) > fm <- lm(depression ~ weight, data=roller) > plot( depression ~ weight, data=roller, type="n") > abline(fm) > attach(roller) > points( depression~weight, subset=1:7) > points( depression~weight, subset=8:10, col="blue") Error in if (length(x) == l) x[s] else x :

Dear all, I want to use aggregate.formula to conveniently summarize a data.frame. I have quiet some variables in the data.frame and thus I don't want to write all these names by hand, but instead create them on the fly. This approach has the advantage that if there will be even more columns in the data.frame I don't have to change the code. I've hence tried to construct a formula

R-list, 1. Given a formula (f) w variables referencing some data set (dat), is there any easier/faster way than this to get the names (in character form) of the variables on the RHS of '~' ? dat <- data.frame(x1 = x1 <- rnorm(100,0,1), x2 = x2 <- rnorm(100,0,1), y = x1 + x2 + rnorm(100,0,1)) f <- y ~ x1 + x2 mf <- model.frame(f, data=dat) mt <- attr(mf,

Dear List I am getting an error when checking my analogue package with R2.10.0-patched. The error comes when running a function within which I use the standard non-standard evaluation method. I've distilled the error and functions involved out into the following simple example to illustrate the error: ## Dummy data to illustrate formula method d <- data.frame(A = runif(10), B = runif(10),

Hi All, I have a formula which has a factor with NAs in it. I wish to keep these in the model matrix, but the NA information is currently lost (the rows are kept but the NA gets converted to 0). Any ideas as to how I can keep NAs in? e.g. junk <-

Dear List, I am writing a formula method for a function in a package I maintain. I want the method to return a data.frame that potentially only contains some of the variables in 'data', as specified by the formula. The problem I am having is in writing the function and wrapping it around model.frame. Consider the following data frame: dat <- data.frame(A = runif(10), B = runif(10), C

Hello guys, I'm trying to do a pairs trading cointegration analysis on two stocks (AXAP and AXANY), but I get an error that I don't understand... Here's my code: setwd("S:/Users/Alexis/Desktop/Essai") #chemin du dossier contenant les donn?es donnees <- read.csv("Data_R.csv", head=T, sep=";", stringsAsFactors=F) library(xts) dates <-