similar to: name of object in quotes

I am getting a difference in results when running some analysis using by and tapply compare to using a for loop. I've tried searching the web but had no luck with the keywords I used. I've attached a simple example below to illustrates my problem. I get a difference in the mean of yvar, diff and the p-value using tapply & by compared to a for loop. I cannot see what I am doing wrong.

Dear R users: I am not entirely convinced that clogit gives me the correct result when I use pspline() and maybe you could help correct me here. When I add a constant to my covariate I expect only the intercept to change, but not the coefficients. This is true (in clogit) when I assume a linear in the logit model, but the same does not happen when I use pspline(). If I did something similar

Dear users, I have a double for loop that does exactly what I want, but is quite slow. It is not so much with this simplified example, but IRL it is slow. Can anyone help me improve it? The data and code for foo_reg() are available at the end of the email; I preferred going directly into the problematic part. Here is the code (I tried to simplify it but I cannot do it too much or else it

I am running R version 2.15.1 in Windows XP I am having problems with a function I'm trying to create to: 1. subset a data.frame based on function arguments (colname & parmname) 2. rename the PARMVALUE column in the data.frame based on function argument (xvar) 3. generate charts plotvar <- function(parentdf,colname, parmname,xvar,yvar ){ subdf <-

I have the following code: ``` rm(list=ls()) N = 30000 xvar <- runif(N, -10, 10) e <- rnorm(N, mean=0, sd=1) yvar <- 1 + 2*xvar + e plot(xvar,yvar) lmMod <- lm(yvar~xvar) print(summary(lmMod)) domain <- seq(min(xvar), max(xvar))??? # define a vector of x values to feed into model lines(domain, predict(lmMod, newdata = data.frame(xvar=domain)))??? # add regression line, using

Hi, I have a large dataframe than I'm writing functions to explore, and to reduce cut and paste I'm trying to write a function that does a subset and then a plot. Firstly, I can write a wrapper around a plot: plotwithfits <- function(formula, data, xylabels=c('','')) { xyplot(formula, data, panel = function(x,y, ...) { panel.xyplot(x,y,

Dear All I am reposting because I my problem is real issue and I have been working on this. I know this might be simple to those who know it ! Anyway I need help ! Let me clear my point. I have huge number of datapoints plotted using either base plot function or xyplot in lattice (I have preference to use lattice). name xvar p 1 M1 1 0.107983837 2 M2 11

Dear all; Is there any way to make this to work?: .x<-rnorm(50,10,3) .y<-.x+rnorm(50,0,1) X<-data.frame(.x,.y) colnames(X)<-c("Xvar","Yvar") Ytext<-"Yvar" lm(Ytext~Xvar,data=X) # doesn't run lm(Yvar~Xvar,data=X) # does run The main idea is to use Ytext as input in a function, so you just type "Yvar" and the model should fit....

Dear users, By running the script below, R crashes systematically at the last command, namely dev.off(), on Windows 7, but not on Windows XP. I therefore don't provide a reproducible example and do not really extract the relevant parts of the script because it has most likely nothing to do with the script itself. I can do it though if you think it might be relevant. R crashes on Windows

Hi,   I have a system in which I analyze 2 subjects and 1 variable, so I have 2 models as follow:   y ~ x_1[, 1] + x_2[, 1] + x_1[, 2] + x_2[, 2]   Where   x_1[, i] = cos(2 * pi * t / T_i) x_2[, i] = sin(2 * pi * t / T_i)   i = 1, 2   Data have two columns: t and y.   As you can see, I have a multiple components model, with rithm and without trends, and I have a fundamental

Hi there, Could someone help me with the following programming problem..? I have written a function that works for my intended purpose, but it is quite closely tied to a particular dataframe and the names of the variables in this dataframe. However, I'd like to use the same function for different dataframes and variables. My problem is that I'm not quite sure how to tell my function in

Hi, this is not a new doubt, but is a doubt that I cant find a good response. Look this output: > m.lme <- lme(Yvar~Xvar,random=~1|Plot1/Plot2/Plot3) > anova(m.lme) numDF denDF F-value p-value (Intercept) 1 860 210.2457 <.0001 Xvar 1 2 1.2352 0.3821 > summary(m.lme) Linear mixed-effects model fit by REML Data: NULL AIC BIC

Hi Everybody I use R2.8.0 on Mac OS X. I set up LyX 1.6.1 to use Sweave today. I can compile the test file I found on CRAN ( http://cran.r-project.org/contrib/extra/lyx/) without a problem and the output looks very nice. In the test file the following R code is used. <<myFirstChunkInLyX>>= xObs <- 100; xMean <- 10; xVar <- 9 x <- rnorm(n=xObs, mean=xMean, sd=sqrt(xVar))

Dear R users, Here is my problem: # example data name <- c(paste ("M", 1:1000, sep = "")) xvar <- seq(1, 10000, 10) set.seed(134) p <- rnorm(1000, 0.15,0.05) dataf <- data.frame(name,xvar, p) plot (dataf$xvar,p) abline(h=0.05) # I can know which observation number is less than 0.05 which (dataf$p < 0.05) [1] 12 20 80 269 272 338 366 368 397 403 432 453

Colleagues, I am fitting an Emax model using nls. The code is: START <- list(EMAX=INITEMAX, EFFECT=INITEFFECT, C50=INITC50) CONTROL <- list(maxiter=1000, warnOnly=T) #FORMULA <- as.formula(YVAR ~ EMAX - EFFECT * XVAR^GAMMA / (XVAR^GAMMA + C50^GAMMA)) ## alternate version of formula FORMULA <- as.formula(YVAR ~ EMAX - EFFECT / (1 + (C50/XVAR)^GAMMA)) FIT <-

Dear list, I would like to do some calculation using different grouping variables. My 'df' looks like this: # Some data set.seed(345) id <- seq(200,400, by=10) ids <- sample(substr(id,1,1)) group1 <- rep(1:3, each=7) group2 <- rep(1:2, c(10,11)) group3 <- rep(1:4, c(5,5,5,6)) df <- data.frame(id, ids, group1, group2, group3) df <- rbind(df, df, df) df$time <-

Hi, Based on some modification that I did to the R Cookbook Graphs Scatterplots code, link:http://wiki.stdout.org/rcookbook/Graphs/Scatterplots%20(ggplot2) I have some questions and I will appreciate a help: - How do I change the legend title? - How can I change the for each linear regression its color and linetype? - How can I add for both the linear regression lines their equations and Rseq

Dear R listers, I am trying to create a lattice plot with independent regression lines per group for each panel, plus one overall regression line per panel. I succeed in having the separate regression lines for each group per panel, but I can't figure out how to add the overall regression line over all groups. I have learnt a lot from the list, but I can't find an example for what I want

Hello together, I am an absolute noob in R and therefore I need help urgently. I have received a script from my tutor with plot functions in it. However, I can' manage to adapt these plots. The hole script is as follows: setwd("E:/") ##### (1) Read data ### dat <- read.table("Komfort_Tatsaechliche_ID_Versuchsreihe_1.txt", header=TRUE, sep="\t",

In ?xy.coords it says: If 'y' is missing and 'x' is a formula: of the form 'yvar ~ xvar'. 'xvar' and 'yvar' are used as x and y variables. list: containing components 'x' and 'y', these are used to define plotting coordinates. time series: the x values are taken to be 'time(x)' and the y