similar to: fittin a regression line

Dear R People: I am drawing graphs for a College Algebra class. I would like to have the x and y axes, along with the lines that I am plotting. So I leave off the axes, and use xlim and ylim. Then I add my abline(v=0). However, I would like to have tick marks on the abline. How would I do that, please? Thanks in advance! Sincerely, Erin M. Hodgess, Ph.D. Associate Professor Department of

If so, I''ve had trouble finding it. Can anyone help?

Hello guys, I am a total newbie on R, having downloaded it, read the documentation and started playing with it right now. My general question is what 'lr' model can be used for doing a linear regression on points that have a variance associated with them (ie. Monte Carlo simulation results). Actually my Data sets look like: Timestep Energy Variance_of_the_Energy 0.0005 -14.876840

Dear all, I have the following output generated by linear regression. Since there is only one regression intercept and one slope for one set of data, what is the meaning of std. error for intercept and that of slope? Thanks in advance. Sincerely, Minghua > data(thuesen) > attach(thuesen) > lm(short.velocity~blood.glucose) Call: lm(formula = short.velocity ~ blood.glucose)

Dear List, I'd like to run a discriminate analysis on a data set, but have no idea how to go about this in R. I have attempted to locate info in the manuals, but may not be consulting the right sections or documents. Can anyone point me to appropriate documentation if such exists. Many thanks, David S. David White sdavidwhite at bigfoot.com Columbus, Ohio

Here's a nasty one. The following has caused a segmentation fault and possibly also a bus error. fred <- 1:6 dim(fred) <- 6 dimnames(fred) <- list(LETTERS[1:6]) mm <- matrix(1:12, 2, 6) mm %*% fred # segmentation fault here In the case without the dimnames assignment the result is OK. Cheers, Jonathan. --please do not edit the information below-- Version: platform =

Please, I would like to know how to generate a truncated multivariate normal distribution k - dimensional, X ~ NT(mu, Sigma), where the elements of X to be non-negative (except the first), and the first dimension is strictly larger than zero. Example: X ~ NT_2(mu, Sigma), where mu=c(0.5, 0.5) and Sigma=c([120, 191], [191,154]), with X_1>0 and X_2>=0 Could anybody help

I have a general style question about R coding. Suppose I'm writing a function (foo1) that calls other functions (foo2, foo3, ...) which have complicated argument lists (e.g. optim(), plot()), _and_ I may be calling several different functions in the body of foo1. Since foo2 and foo3 have different sets of arguments, I can't just use "..." ; I did write some code a while ago

R help list subscribers, I am a new user of R. I am attempting to use R to explore a set of equations specifying the dynamics of a three trophic level food chain. I have put together this code for the function that is to be evaluted by LSODA. My equations Rprime, Cprime, and Pprime are meant to describe the actual equation of the derivative. When I run LSODA, I do not get the output that

Dear all I am trying to compare the performances of several methods using the AUC0.1 and not the whole AUC. (meaning I wanted to compare to AUC's whose x axis only goes to 0.1 not 1) I came to know about the Mcneil Hanley test from Bernardo Rangel Tura and I referred to the original paper for the calculation of "r" which is an argument of the function cROC. I can only find the

Dear RHelpers, Does anyone know of any R code to perform bivariate Poisson regression (including random effects)? Best wishes Simon Simon D.W. Frost, M.A., D.Phil. Department of Pathology University of California, San Diego Antiviral Research Center (Formerly: UCSD Treatment Center) 150 W. Washington St., Suite 100 San Diego, CA 92103 USA Tel: +1 619 543 8080 x275 Fax: +1 619 298 0177 Email:

Dear R-help, Can some one tell me how to do the following (if it's possible)? Suppose I have a function like this: f <- function(x, y, ...) { ## some code g(x, y, ...) ## some more code } The problem is that g() may not understand everything that comes through in "...". Is there a way to delete some component of "..." and then pass it to g()? Here's

Dear all, I try to compare the performances of several parameters to diagnose lameness in dogs. I have several ROC curves from the same dataset. I plotted the ROC curves and calculated AUC with the ROCR package. I would like to compare the AUC. I used the following program I found on R-help archives : From: Bernardo Rangel Tura Date: Thu 16 Dec 2004 - 07:30:37 EST

I'm trying to get a grasp of maximum-likelihood estimation and would like to find a package that performs mle (hopefully a simple example). It seems as if there are plenty of packages that make use of different types of likelihood estimators, but none are of a simple, "newbie" type. Does anyone have a suggestion for which package would be the best for a mle example? Thanks, Jeff.

I might be missing something but I thought that AUC was a measure for comparing ROC curves, so there is nothing else needed to "compare" them. The larger AUC is the higher correlation of 2 variables compared. No other measures or calculations are needed. Jarek Tuszynski -----Original Message----- From: r-help-bounces at stat.math.ethz.ch [mailto:r-help-bounces at stat.math.ethz.ch] On

I'm probably missing something very basic here, but: I've written some C code that I load into R dynamically. In the course of this C code, I generate some multinomial random deviates. I initially used the publically available "randlib" library, which also implements its own random number generator and binomial deviates (which are used to generate the multinomial deviates).

Dear all, I found that the new feature of the comment.char="#" argument in the read.table function truncated my data while the data set actually contains '#'. We analyze lot of data that contain '#'. This is really annoying and it is also not compatible earlier version of R. I searched the R archive and found the following message for the scan function. Is it

I have two CSV files (exported from Excel), say file1 and file2. The have the same number of rows, and each has several columns, with names on the first line; and some of the columns in file1 are repeated in file2. Using the "foreign" package, I can read these in separately to dataframes say d1 and d2 with > d1<-read.csv("file1") >

How do I add error bars to an interaction plot of means? Thanks

Hey, all I am going to plot several 3-dimensional ellipsoids in R. For example, A is such a ellipsoid with mean u=[1 1 1]', covariance matrix C=[1 0 .5;0 1 .6;.5 .6 1]; So how can I plot such object in 3D space? Is there some function to achieve this? Thanks. Fred