similar to: p value statistic for lm object

Hello. I would like to know how to set the image() function so that it assigns colors relative to an absolute scale, as opposed to relative to the values present in a particular call to image(). For example: m <- matrix(1:18,3,6) par(mfrow = c(2,1)) image(1:6, 1:3, t(m), col = rainbow(20)) image(1:6, 1:3, t(m+9), col = rainbow(20)) Then the two images are identical. But the right

Hi all: Here's a question about result of loglinear analysis. There're 2 factors:area and nation.The raw data is in the attachment. I fit the saturated model of loglinear with the command: glm_sat<-glm(fre~area*nation, family=poisson, data=data_Analysis) After that,I extract the coefficients: result_sat<-summary(glm_sat) result_coe<-result_sat$coefficients I find that all the

Dear R users, I'm trying to automatically generate a *.tex file with the output of an OLS estimation. Some people suggested to use the latex function on the Hmisc package. I'm having a bit of trouble to properly specify this function (I'm not a very experienced R user). Below you will find an example, of what I'm doing. ## Annette Dobson (1990) "An Introduction to Generalized

I ran across this error the other day while using lm(). I confess that I haven't used it for awhile and haven't been tracking the changes between versions of R. However, the piece of code below is a tiny modification of the example in the help file for "lm". I just separated the commands apart for clarity. A similar piece comes from the help file for

Hi, I am wondering if there is a way to display the full anme of the regression coeffients/factors in the summary? Suppose I have a bogus data set using weekday as factor which has 7 levels such as: mydata <- sample(364) wk <- rep(1:7, 52) weekday <-

I am trying to store regression objects in a data.table df <- data.frame(x = rnorm(20)) df[, "y"] <- with(df, x + 0.1 * x^2 + 0.2 * rnorm(20)) mydt <- data.table(mypower = c(1, 2), myreg = list(lm(y ~ x, data = df), lm(y ~ x + I(x^2), data = df))) mydt #?? mypower??? myreg #???? <num>?? <list> #1:?????? 1 <lm[12]> #2:?????? 2 <lm[12]> But mydt[1, 2]

Hello, I am interested in plotting my regression analysis results(regression coefficients and standard errors obtained through OLS and Tobit models) in the form of graphs.What is the best way to accomplish this? Thanks. Murali Kuchibhotla [[alternative HTML version deleted]]

General question concerning summary results of a linear model. I've tried to look in help and search online but I either don't understand it or I can't find the answer. I've defined a model with a really large number of variables and levels. The summary results are so big that not all of the coefficients etc can be displayed completely in the console. I try to scroll back and

I think I have isolated a problem with integration between Sweave and beamer. Could you please see the file: http://www.mayin.org/ajayshah/tmp/bugdemo.Rnw Unfortunately, it uses some of my internal libraries, so you can't run it. When I put it through Sweave, I get: http://www.mayin.org/ajayshah/tmp/bugdemo.tex which is, of course, a generic latex file which you can read and

Dear R-users, I'm finding for a R-package concerning graphs. Is there some kind of that package? I've a set of correlation coeffients between several variable and I wish to built a graph to link variables correlated. Many thanks. Best, Vito ===== Diventare costruttori di soluzioni "The business of the statistician is to catalyze the scientific learning process." George

Hello , I want to compare two quadratic regression models with non-parametric bootstrap. However, I do not know which R package can serve the purpose, such as boot, rms, or bootstrap, DeltaR. Please kindly advise and thank you. Elaine The two quadratic regression models are y1=a1x^2+b1x+c1 y1= observed migration distance of butterflies() y2=a2x^2+b2x+c2 y2= predicted migration distance of

Dear Everyone in list: I am writing some codes to automate the process of fitting linear models where the names of variables of models are produced and stored in character vectors. But I have problems to pass the vectors to the lm( ) because I don't know how to strip the quotation marks automatically. Here are the codes of the example of lm( ): ## Annette Dobson (1990) "An Introduction

Hi I am having problems with machine authentication on an NT workstation 4.0 SP6a client. The current version of samba is 2.0.4b complied on Sequent/Dynix 4.4.8. We are using "smbd" and "nmbd" as services launched from the inetd file. No restrictive or secure components have been enabled. The "smb.conf" simply has the appropriate mount options defined. The problem

Sirs, I am a newbe jumping to advance routing and traffic control. I work for one of the leading isp in kingdom of Nepal. My goal is to do bandwidth management for our lease line customer so that they could use their allocated bandwidth only. Bgp and ospf is implemented as a routing protocol. All routers are cisco routers. There are about 16 routers some are with highly danced ports. No Linux box

Dear list, I was wondering if it is possible to get the p-values for one-sided tests on the parameters of a linear regression. For instance, I use lm() and store the result in an object. lm() gives me a matrix, using summary() and coef() on which gives me a matrix containing the coefficients, the standard errors, the t-statistics and the two-sided p-values by default. Can I get it to provide me

Well, you may have good reasons to do things this way -- and you certainly do not have to explain them here. But you might wish to consider using R's poly() function and a basic nested list structure to do something quite similar that seems much simpler to me, anyway: x <- rnorm(20) df <- data.frame(x = x, y = x + .1*x^2 + rnorm(20, sd = .2)) result <- with(df,

I've been writing a bunch of simulation experiments to test models in MASS (glm.nb) and JK Lindsey's repeated library (gar and kalcount). If I generate data over and over, and estimate a model for each, I end have syntax like this: x <- rnorm(1000) for (i in 1: nOfRuns){ y <- getPhonyData(x) estim <- glm.nb(y~x,link="log") } Except for problems of nonconvergence

Hi! Can anyone tell me how to convert the anova/ancova summary output into a data frame? Thanks! Shane Phillips [[alternative HTML version deleted]]

Thanks everyone for their responses. My data is organized in a data.table.? My goal is to perform analyses according to some groups.? The results of analysis are objects.? If these objects could be stored as elements of a data.table, this would help downstream summarizing of results. Let me try another example. carsdt <- setDT(copy(mtcars)) carsdt[, unique(cyl) |> length()] #[1] 3

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