similar to: question re: "summarry.lm" and NA values

Dear Sir or Madam, I am a student at MSc Probability and Finance at Paris 6 University/ Ecole Polytechnique. I am using R and I can't find an answer to the following question. I will be very thankful if you can answer it. I have two vectors rendements_CAC40 and rendements_AlcatelLucent. I use the lm function as follows, and then the sumarry function: regression=lm(rendements_CAC40 ~

I am using R in a Windows environment. I have a basic question regarding lm(). I have a dataframe ?data1? with ncol=w. I know that my dependent variable is in column1. Is there a way to write the regression formula so that I can use columns 2 thru w as my independent variables? e.g. something like: ? lm(data1[,1] ~ data1[,2:w] ) ? Thanks

Hi there, I am trying to use linear regression to solve the following equation - y <- c(0.2525, 0.3448, 0.2358, 0.3696, 0.2708, 0.1667, 0.2941, 0.2333, 0.1500, 0.3077, 0.3462, 0.1667, 0.2500, 0.3214, 0.1364) x2 <- c(0.368, 0.537, 0.379, 0.472, 0.401, 0.361, 0.644, 0.444, 0.440, 0.676, 0.679, 0.622, 0.450, 0.379, 0.620) x1 <- 1-x2 # equation lmFit <- lm(y ~ x1 + x2) lmFit Call:

I have a dataset of 3 ?columns? and 5 ?rows?. temp<-data.frame(col1=c(5,10,14,56,7),col2=c(4,2,8,3,34),col3=c(28,4,52,34,67)) I wish to convert this to a single ?column?, with column 1 on ?top? and column 3 on ?bottom?. i.e. 5 10 14 56 7 4 2 8 3 34 28 4 52 34 67 Are there any functions that do this, and that will work well on much larger datasets (e.g. 1000 rows, 6000 columns)?

>>>>> Martin Maechler <maechler at stat.math.ethz.ch> >>>>> on Thu, 14 Sep 2017 10:13:02 +0200 writes: >>>>> Fox, John <jfox at mcmaster.ca> >>>>> on Wed, 13 Sep 2017 22:45:07 +0000 writes: >> Dear Terry, >> Even the behaviour of lm() and glm() isn't entirely consistent. In both cases,

Dear all, I have been working on an idempotent version of apply, such that applying a function f(x) = x (ie. force) returns the same array (or a permutation of it depending on the order of the margins): a <- array(1:27, c(2,3,4)) all.equal(a, iapply(a, 1, force)) all.equal(a, iapply(a, 1:2, force)) all.equal(a, iapply(a, 1:3, force)) all.equal(aperm(a, c(2,1,3)), iapply(a, 2, force))

Hello, I am VERY new to R (one week) and I am trying to run a multinomial logit model. The model I am using is > model1 <- multinom(Y ~ X1 + X2 + , ..., Xn) if I put in > summary(model1) I get #Error in function (classes, fdef, mtable) : unable to find an inherited method for function "fitted", for signature "multinom" and if I put in > coef(model1)

Dear Terry, Even the behaviour of lm() and glm() isn't entirely consistent. In both cases, singularity results in NA coefficients by default, and these are reported in the model summary and coefficient vector, but not in the coefficient covariance matrix: ---------------- > mod.lm <- lm(Employed ~ GNP + Population + I(GNP + Population), + data=longley) >

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())

I have a large dataset grouped by a factor and I want to perform a regression on each data subset based on this factor. There are many ways to do this, posted here and elsewhere. I have tried several. However I found one method posted on the R wiki which works exactly as I want, and I like the elegance and simplicity of the solution, but I don't understand how it works. Its all in the formula

Hi all I'm trying to use the 'by' function to extract the co-efficients from a mixed model which is performed on multiple individuals. I basically have a group of individuals and for each individual I want the co-efficient for there change in 'pots_hauled' in response to a change in 'vpue' with my random variable being 'ns_a_vpue'. The problem I am having is

Hello, I am using the lm to fit a linear model to data, I was wondering if there is a way to display the equation on a plot using the extracted lm coefficients? I am using the plot() function to create the plot/.png. Example: lm_mod <- lm(data1~data2) intercept = 48.54 slope = 0.4856 I want to display equation on a plot as y=0.4856x+48.54 Any thoughts or suggestions are appreciated.

R-1.7.0 built on NetBSD 1.6, but the validation test suite failed: Machinetype: Intel Pentium III (600 MHz); NetBSD 1.6 (GENERIC) Remote gcc version: gcc (GCC) 3.2.2 Remote g++ version: g++ (GCC) 3.2.2 Configure environment: CC=gcc CXX=g++ LDFLAGS=-Wl,-rpath,/usr/local/lib make[5]: Entering directory `/local/build/R-1.7.0/src/library' >>> Building/Updating

Please I getting some erros about SPNs and main process ended respawing, bellow the erros that ia m getting at messages log 5 or more machines are getting "Failed to modify SPNs on CN=PC-2902194,OU=XXXXX ,DC=ABC,DC=com,DC=br: error in module acl: Constraint violation (19)" another problem is more serious ... I really need help because the main process of Samba4 is respawing... ad

Following Tim's comments, here are my reworked patches for the Neon intrinsic function patches of of my Aarch64 patchset, i.e. replacing patches 5-8 of the v2 series. Patches 1-4 and 9-18 of the old series still apply unmodified. The one new (as opposed to changed) patch is the first one in this series, to add named constants for the ARM architecture variants. There are also some minor code

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 All, I'm having trouble with the automatized model generation (dredge) function in the MuMIn package. I'm trying to use it to automatically generate subsets of models from a global cox proportional hazards model, and rank them based on AICc. These seems like it's possible, and the Mumin documentation says that coxph is supported. However, when I run the code (see below), it gives

I am using R 2.1.1 in an windows XP environment. I have 2 dataframes, temp1 and temp2. Each dataframe has 20 variables (“cocolumns") and 525 observations (“rows”). All variables are numeric. I want to create a new dataframe that also has 20 columns and 525 rows. The values in this dataframe should be the sum of the 2 other dataframe. (i.e. temp1$column

I am using the scan command to read a file I called data1. The program returns Error in file(file,"r") : unable to open connection In addition: Warning message: cannot open file 'data1' I already checked to see if the starting directory in R was correct and it is. Also, the file opens ok from its directory so it isn't corrupted. Does someone