similar to: Pre-OLS attempt for (xen)linux directory structure convergence

Folks, OLS is fast approaching. There is a session on virtualization at the Kernel Summit, with Keir and Zach invited, which will probably last an hour(?). There is also a Xen BoF currently scheduled (Thursday, 7/20, 7:00PM) which will cover Xen specific issues. And there are approximately 3 or 4 paper presentations on related subjects. None of the above are going to allow for adequate time to

Folks, Regarding the Virtualization BoF, Ted Tso clarified that the remaining BoF sessons would just be scheduled on paper at OLS. We only need to use a scheduled BoF slot if we want to use a room there, I guess, else we can schedule at any free time and use a corridor or pub. Available BoF slots are only Friday evening, note. Since I don't believe the Xen team is available Friday evening,

Dear all, When fitting an "ols.model", the confidence interval at 95% doesn't cover the plotted data points because it is very narrow. Does this mean that the model is 'overfitted' or is there a specific amount of serial correlation in the residuals? Which R functions can be used to evaluate (diagnostics) major model assumptions (residuals, independence, variance) when

Hi! I need to run ols regressions with Huber-White sandwich estimators and the correponding standard errors, without an intercept. What I'm trying to do is create an ols object and then use the robcov() function, on the order of: f <- ols(depvar ~ ind1 + ind2, x=TRUE) robcov(f) However, when I go f <- ols(depvar ~ ind1 + ind2 -1, x=TRUE) I get the following error: Error in

Hi everyone, I'm having some difficulty getting "simple effects" for the ols() function in the rms package. The example below illustrates my difficulty -- I'll be grateful for any help. #make up some data exD <- structure(list(Gender = structure(c(1L, 2L, 1L, 2L, 1L, 1L, 1L, 2L, 1L, 2L, 2L, 2L, 1L, 2L), .Label = c("F", "M"), class = "factor"),

Hello, I have a couple of questions about the ols function in Frank Harrell's rms package. Is there any way to specify variables by their column number in the data frame rather than by the variable name? For example, library(rms) x1 <- rnorm(100, 0, 1) x2 <- rnorm(100, 0, 1) x3 <- rnorm(100, 0, 1) y <- x2 + x3 + rnorm(100, 0, 5) d <- data.frame(x1, x2, x3, y) rm(x1, x2, x3,

I am trying to extract significance levels out of a robcov+ols call. For background: I am analysing data where multiple measurements(2 per topic) were taken from individuals(36) on their emotional reaction (dependent variable) to various topics (3 topics). Because I have several emotions and a rotation to do on the topics, I'd like to have the results pumped into a nice table.

Hello everybody! I am currently using the quantreg package on R 2.2.1. for my diploma thesis and want to create plots with plot.summary.rqs, which should work like this: Usage: plot.summary.rqs(x, nrow=3, ncol=2, alpha = 0.1, ols = TRUE, ...) Arguments: x: an object produced by rq() fitting nrow: rows in mfrow ncol: columns in mfrow alpha: alpha level of

Hi folks! Does anybody know how to use the OLS function in fMultivar to do dynamic regression? I've tried specifying lags in OLS using a data series created in fSeries and it doesn't seem to work. I've done dynamic regression using dyn$lm and I was wondering how to accomplish the same thing using the OLS function from fMultivar. Thanks! John [[alternative HTML version

Hello, I have a question about the ?plot.predict? function in Frank Harrell's rms package. Do you know how to superpose in the same graph the prediction curve of ols and raw data points? Put most simply, I would like to combine these two graphs: > fit_linear <- ols (y4 ~ rcs(x2,c(5,10,15,20,60,80,90)), x=TRUE, y=TRUE) > p <- Predict(fit_linear,x2,conf.int=FALSE) > plot (p,

Dear R help, I'm having some trouble with model formulas for the ols function in the rms package. I want to have two variables represented as restricted cubic splines, and also include an interaction as a product of linear terms, but I get an error message. library(rms) d <- data.frame(x1 = rnorm(50), x2 = rnorm(50), y = rnorm(50)) ols(y ~ rcs(x1,3) + rcs(x2,3) + x1*x2, data=d) Error in

How can I extract the adjusted R^2 value from an ols object (using rms package)? library(rms) x <- rnorm(10) y <- x + rnorm(10) ols1 <- ols(y ~ x) Typing "ols1" displays adjusted R^2 among other things, but how can I assign it to a variable? I tried str(ols1) but couldn't see where to go from there. Thanks, Mark Seeto

Hello I am facing a curious problem.I have a time series data with which i want to fit auto-regressive model of order p, where p runs from 1:9.I am using a for loop which will fit an AR(p) model for each value of p using the *ar.ols* function. I am using the following code for ( p in 1:9){ a=ar.ols (x=data.ts, order.max=p, demean=T, intercept=T) } Specifying the *order.max* to be p, it gives me a

Dear All, I'm trying to use the ols function in the Design library (version 2.1.1) of R to estimate parameters of a linear model, and then use the contrast function in the same library to test various contrasts. As a simple example, suppose I have three factors: feature (3 levels), group (2 levels), and patient (3 levels). Patient is coded as a non-unique identifier and is

Hi, I'm trying to use Frank Harrell's Design:::ols function to do regression of y (numeric) on the interaction of two factors (x1 and x2), but Lapack throws an error: > library(Design) ... > load(url("http://www.csse.unimelb.edu.au/~gabraham/x")) > ols(y ~ x1 * x2, data=x) Error in chol2inv(fit$qr$qr) : 'size' cannot exceed nrow(x) = 20 > traceback()

I might be sorry for asking this question :-) I have two equations and I tried to estimate them individually with "lm" and "gls", and then in a system (using systemfit) with "OLS", "WLS" and "SUR". Quite surprisingly (for myself at least) the results are identical to the last digit. Could someone (please!) give a hint as to what am I

A while ago (I think at the Xummit), I recall someone saying that the structure of the files in xenlinux may change soon so that the xen-specific files would move to a subdirectory or arch/<arch> (e.g. linux/arch/i386/xen instead of linux/arch/xen/i386). Is this still planned? If so, what is the timing? If it''s in progress, I''d like to get in the loop... Thanks, Dan

Hi, I have 142 observations off different variables and I'm trying to do a OLS. And I get this error. Any Ideas ? > f <- ols(lnmigr3~popden78+income+modern+spareha+rain) Error in La.chol2inv(x, size) : size cannot exceed nrow(x) = 1 D. ----------------------------------------- Stay ahead of the information curve. Receive GIS news and jobs on your desktop daily. Subscribe today

Hello R-list, I am trying to calculate a ridge regression using first the *lm.ridge()* function from the MASS package and then applying the obtained Hoerl Kennard Baldwin (HKB) estimator as a penalty scalar to the *ols()* function provided by Frank Harrell in his Design package. It looks like this: > rrk1<-lm.ridge(lnbcpc ~ lntex + lnbeerp + lnwinep + lntemp + pop, subset(aa,

I have installed Hmisc and Design. When I use ols, I get the following error message: Error in if (!length(fname) || !any(fname == zname)) { : missing value where TRUE/FALSE needed The model that I am running is: > ecools <- ols(eco$exp ~ eco$age + eco$own + eco$inc + inc2, x=TRUE) I have tried several other combinations of arguments that take TRUE/ FALSE values, but no luck.