similar to: Bootstrapped Regression

Hello Rui, Thanks for your helpful suggestions. Just for illustration, let's use the well known Duncan dataset of prestige vs education + income that is contained in the "car" package. Suppose I wish to use boot function to bootstrap a linear regression of prestige ~ education + income and use the following script: duncan.function <- function(data, indices) {data =

Hello, Much clearer now, thanks. It's a matter of changing the function boot calls to return the predicted values at the point of interess, education = 50, income = 75. I have changed the way the function uses the indices a bit, the result is the same, it's just the way I usually do it. pred.duncan.function <- function(data, indices) { mod <- lm(prestige ~ education +

R-help is not a free coding service. We expect users to make the effort to learn R and *may* provide help when they get stuck. Pay a local R programmer if you do not wish to make such an effort. Cheers, Bert On Oct 14, 2017 7:58 AM, "Janh Anni" <annijanh at gmail.com> wrote: Greetings! We are trying to obtain confidence and prediction intervals for a predicted Y value from

Dear All, I have two simple data samples (no groups or factors, etc.) and would just like to compute the two-sample Wilcoxon Rank Sum test using the wilcox_test function contained in the coin package, which is reportedly better than the regular wilcox.test function because it performs some adjustment for ties. Would anyone know how to craft a script to perform this task? Much appreciated. Janh

Dear Users Regarding the NADA package, would anyone be able to help me understand what values are actually plotted on the Y axis of the plot obtained by using the *ros* function on the data and plotting the result with the plot() function? The Y axis is labeled "Values". According to the NADA user manual, ros performs a log transformation of the data by default, but the user can specify

Hello All, Would anyone be able to help me understand how R computes a quantile-quantile plot for comparing two data samples with unequal sample sizes? Normally, the procedure should be to rearrange the larger data sample into n equally-spaced parts using interpolation, where n is the sample size of the smaller sample, and then plot the matching data pairs. I tried using different plotting

Hi, I try to boxplot following data on the subset of (V1,V3,V5,V7) and (V2,V4,V6,V8) V1 V2 V3 V4 V5 V6 V7 V8 2 4 6 7 12 33 43 53 how can I use boxplot function to plot it? thanks, William

Dear R-devel list members, I'd like to suggest a more flexible procedure for generating contrast names. I apologise for a relatively long message -- I want my proposal to be clear. I've never liked the current approach. For example, the names generated by contr.treatment paste factor to level names with no separation between the two; contr.sum simply numbers contrasts (I recall an

Dear R list members, I'm encountering a problem with expand.model.frame(): Suppose that I define the following simple function (meant just to illustrate the problem): > fun <- function(model){ + expand.model.frame(model, all.vars(formula(model))) + } > and I have the following model, created with an explicit data argument: > mod Call:

R 2.2.0 windows XP How can I perform a regression analyses using a vector of means, a variance-covariance matrix? I looked at the help screen for lm and did not see any option for using the afore mentioned structures as input to lm. Thanks, John John Sorkin M.D., Ph.D. Chief, Biostatistics and Informatics Baltimore VA Medical Center GRECC, University of Maryland School of Medicine Claude D.

I noticed that when I fit a linear model using 'lm' there is an attribute called "factors" that is added to the "term". It doesn't seem to appear for 'model.matrix', just 'lm'. I have been unable to find where it gets constructed or what it means? It looks like a two dimensional array that I may be able to use so I would just like to get some

Greetings all! Got another question for you: When doing regression, is there a way of automatically obtaining the standardized correlation coefficients? /Fredrik -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the

This is my first post to this list so I suppose a quick intro is in order. I've been using SPLUS 2000 and R1.6.2 for just a couple of days, and love S already. I'm reading MASS and also John Fox's book - both have been very useful. My background in stat software was mainly SPSS (which I've never much liked - thanks heavens I've found S!), and Perl is my tool of choice for

Dear List, I don't get scatter3d to color the sheres according to the '|' argument. library(car) scatter3d(prestige ~ income + education|type, data=Prestige) The spheres on my screen are all colored the same and they are not conditional on Prestige$type. On the other hand: Fit3d and Ellipse3d are colored according to the group argument. rgl_0.92.879 car_2.0-12 R version 2.15.0

Hi In the following, the graph I see on the screen and the .png output coincide. However, in the .pdf file, the fonts seem to be scaled fairly larger, resulting in the label for the top legend disappearing. Is this an infelicity or bug, or is there something I've missed? More generally, how do I control the size of fonts used in legends and axis labels? library(car) library(ggplot2) qp

Dear all, I'm trying to use "scatterplot" from package "car" to get a scatterplot with row-names as labels and I want my data to be divided into two groups defined by the column "tresh". Leaving away the groups-command gives me the right labels but they are not distinguished by colors according to "tresh". Does anybody know why the following example

Hi, I would like to use the sem package to perform a path analysis (no latent variables) with a mixture of 2 nominal exogenous, 1 continuous exogenous, and 4 continuous endogenous variables. I seek advice as to how to calculate the appropriate covariance matrix for use with the sem package. I have read through the polycor package, and am confused as to the use of "numeric" for

Buenas tardes   Estoy intentando representar graficamente la elipse de confianza de dos pendiente en un modelo sin intercepto La formula que introduzo esplot(ellipse(recta,c(1,1)),type="l"), pero elipse me sale una recta   Gracias [[alternative HTML version deleted]]

Dear R users, Suppose I have two different response variables y1, y2 that I regress separately on the same explanatory variable, x; sample sizes are n1=n2. Is it legitimate to compare the regression slopes (equal variances assumed) by using lm(y~x*FACTOR), where FACTOR gets "y1" if y1 is the response, and "y2" if y2 is the response? The problem I see here is that the

Thanks to Marc Schultz I found the documentation on the "factors" attribute under ?term.object. It stats: factors: A matrix of variables by terms showing which variables appear in which terms. The entries are 0 if the variable does not occur in the term, 1 if it does occur and should be coded by contrasts, and 2 if it occurs and should be coded via dummy