similar to: scan command

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 trying to plot two density lines on the same graph. Using the functions on the base package, I would go: plot(density(x), col = 1) lines(density(y), col = 2) And I get two distinct (one-bump) density lines. When I try to do it using lattice, I get two two-humped lines. (In other words, I think the smoothing function is taking the next set of data points and smoothing them in the same

This is probably a simple problem but I don't see a solution. I have a data.frame with a number of columns where I would like 0 <- NA thus I have df1[,144:157] <- NA if df1[, 144: 157] ==0 and df1[, 190:198] <- NA if df1[, 190:198] ==0 but I cannot figure out a way do this. cata <- c( 1,1,6,1,1,NA) catb <- c( 1,2,3,4,5,6) doga <- c(3,5,3,6,4, 0) dogb <- c(2,4,6,8,10,

Hello, Is there a way to extract multiple columns from a dataframe using their names instead of their numbers? Currently I use: data2 <- data1[, c(1,3,9)] And I am looking for something like data2 <- data1[, c("XX","YY","ZZ")] I use the same dataframe for many purposes, and I run codes that change the order of the columns every time. Many thanks, Adrian

Hi, I am new to R. I don't have strong background of statistics. I am a student of Geotechnical Engineering. I tried to run a nonlinear regression for a three-variable function, that is N = f(CSR, ev) # N is a function of CSR and ev, and N = CSR/(A +B*CSR), wherer (A,B) are function of ev. N, CSR and ev are observed in the experiments. Following is my R script. rm(list=ls())

Suppose, I have a file "data1" containing: 450 390 467 654 30 542 334 432 421 357 497 493 550 549 467 575 578 342 446 547 534 495 979 479 I can read this file with: scan("data1") Read 24 items [1] 450 390 467 654 30 542 334 432 421 357 497 493 550 549 467 575 578 342 446 [20] 547 534 495 979 479

Hi all, I'm currently working on an R program where I have to access an FTP server to download some of the data I need. However, the people who post up the files I access are at times inconsistent with regards to time posted, if they post at all, etc.... Here's some of the code I use: library(RCurl) url1 = paste("ftp://user:password at a.great.website.com/",

Dear R-users, When i try - Data1<-read.table("/Users/kama/Analysis/GDP10.csv",header=TRUE,sep=";") i am getting this error: Warning message: In scan(file, what, nmax, sep, dec, quote, skip, nlines, na.strings, : number of items read is not a multiple of the number of columns I wonder what Iam doing wrong. i guess it is something simple, however, i do not understand

Dear R-users, I have 1 remark and 1 question on the inclusion of interactions in the gam function from the gam package. I need to fit quantitative predictors in interactions with factors. You can see an example of what I need in fig 9.13 p265 from Hastie and Tibshirani book (1990). It's clearly stated that in ?gam "Interactions with nonparametric smooth terms are not fully

Hello, I'm having problems with samba share and trying to make multiple connections from one PC. Here are the errors I'm seeing in the log file: [2006/12/19 09:02:48, 1] smbd/service.c:make_connection_snum(648) amcfp001 (10.210.4.65) connect to service bvvol02_U1 initially as user bvvol02 (uid=502, gid=502) (pid 17671) [2006/12/19 09:02:48, 1]

Hello R-helpers, I have 10 dataframes (named data1, data2, ... data10) and I would like to add 5 new columns to each dataframe using the following code: data1$LogDepth<-log10(data1[,2]/data1[,4]) data1$LogArea<-log10(data1[,3]/data1[,5]) data1$p<-2*data1[,6]/data1[,7] data1$Exp<-data1[,2]^(2/data1[,8]) data1$s<-data1[,3]/data1[,9] ...but I would prefer not to repeat this chunk of

hello folks, Im trying to clean out a large file with data i dont need. The column im manipulating in the file is called "legal_status" There are three kinds of rows i want to remove. Those that have "Private", "Private (Op", or "Unknown" in the legal_status column. I wrote this code but i get errors and it says im missing a TRUE/ False thingy...im

I am trying to run my first app on the Solaris server, in a production environment. I get a network unreachable. Why? Does it belongs to database.yml config? Processing CategoriesController#index (for 10.3.70.129 at 2010-01-05 14:00:47) [GET] Errno::ENETUNREACH (Network is unreachable - connect(2)): /usr/ruby-enterprise/lib/ruby/1.8/net/http.rb:560:in `initialize''

Hi This question is far less simple than the title suggests, please read carefully, thanks. I have 2 sets of data, both read into R >data1<-read.table ("1.txt", header=T, sep="\t") >data2<-read.table ("2.txt", header=T, sep="\t") >data1 Taxon stage1 stage2 stage3 stage4 T1 0 0 1 1 T2 0

Hi, I apologize if this has previously been posted. I've just subscribed to the R-help digest. I'm writing a plotting function that uses layout() to plot several different plots on the same device. This function uses plot(), image(), and a custom function that uses text(). Each cell of the layout needs different par() parameters, so what I'd like to do is pass them as lists:

Hi there, data1<-matrix(data=c(1,1.2,1.3,"3/23/2004",1,1.5,2.3,"3/22/2004",2,0.2,3.3,"4/23/2004",3,1.5,1.3,"5/22/2004"),nrow=4,ncol=4,byrow=TRUE) data1<-data.frame(data1) names(data1)<-c("areaid","x","y","date") data1 areaid x y date 1 1 1.2 1.3 3/23/2004 2 1 1.5 2.3 3/22/2004 3 2

I am trying to find methods for testing and visualizing calibration to Cox models with time-depended coefficients. I have read this nice article <http://journals.sagepub.com/doi/10.1177/0962280213497434>. In this paper, we can fit three models: fit0 <- coxph(Surv(futime, status) ~ x1 + x2 + x3, data = data0) p <- log(predict(fit0, newdata = data1, type = "expected")) lp

Hello everyone, I am attempting to write a function to count the number of non-missing values of each column in a data frame using the sapply function. I have the following code which is receiving the error message below. > n.valid<-sapply(data1,sum(!is.na)) Error in !is.na : invalid argument type Ultimately, I would like for this to be 1 conponent in a larger function that will produce

I need help in subseting a dataframe: data1<-data.frame(year=c(2001,2002,2003,2004,2001,2002,2003,2004, 2001,2002,2003,2004,2001,2002,2003,2004), firm=c(1,1,1,1,2,2,2,2,3,3,3,3,4,4,4,4),x=c(11,22,-32,25,-26,47,85,98, 101,14,87,56,12,43,67,54), y=c(110,220,302,250,260,470,850,980,1010,140,870,560,120,430,670,540)) data1 I want to keep the firms where all x>0 (where there are

Hi everybody, I'm using the method described here to make a linear regression: http://www.apsnet.org/education/advancedplantpath/topics/Rmodules/Doc1/05_Nonlinear_regression.html > ## Input the data that include the variables time, plant ID, and severity > time <- c(seq(0,10),seq(0,10),seq(0,10)) > plant <- c(rep(1,11),rep(2,11),rep(3,11)) > > ## Severity