similar to: select integer intervals from a integer space

Hello Everyone,   This is my first attempt to do something in R. As a precursor to a Willingness to Pay analysis, I want to conduct a Mixed Conditional Logit analysis but am unsure how to proceed because of some nesting within my data.   Below is some data and code that illustrate what I’m trying to do. The data are based on responses to a conjoint survey obtained during pilot testing. In the

http://www.nabble.com/file/p20332968/spe.dat spe.dat Hi, i have a problem in sorting out some command in R and i am really hoping some expert can help me out please! i have the spe.dat file which i upload here, and when u read into R u got something like this: A5 <- read.table('spe.dat' ,header=TRUE) A5 EXPEND ECAB MET GROW YOUNG OLD WEST STATE 1 256 85.5 19.7 6.9 29.6

>>>>> Josh O'Brien <joshmobrien at gmail.com> >>>>> on Mon, 4 Jan 2016 16:16:51 -0800 writes: > On Dec 19, 2015, at 3:32 AM, Martin Maechler <maechler at stat.math.ethz.ch> wrote: >>>>>>> Martin Maechler <maechler at stat.math.ethz.ch> on >>>>>>> Sat, 12 Dec 2015 10:32:51 +0100

I have already obtained my confidence intervals from a bootstrapping procedure and now I want to plot the estimates and the confidence intervals similar to the plots obtained when the geom_smooth function is used in ggplot2. Thanks -- View this message in context: http://r.789695.n4.nabble.com/Plotting-Confidence-Intervals-with-a-proiri-calculated-Intervals-tp4322581p4322581.html Sent from the R

On Dec 19, 2015, at 3:32 AM, Martin Maechler <maechler at stat.math.ethz.ch> wrote: >>>>>> Martin Maechler <maechler at stat.math.ethz.ch> >>>>>> on Sat, 12 Dec 2015 10:32:51 +0100 writes: > >>>>>> John Chambers <jmc at r-project.org> >>>>>> on Fri, 11 Dec 2015 10:11:05 -0800 writes: >

Hacker's Delight or this web page are probably the best references for tricks like this: https://graphics.stanford.edu/~seander/bithacks.html#CopyIntegerSign John On 03/30/2018 03:58 AM, edA-qa mort-ora-y via llvm-dev wrote: > I'm looking for ways to do some basic operations without using branches. > > The key operation I want is a floored/round-to-negative-infinity integer

I'm looking for ways to do some basic operations without using branches. The key operation I want is a floored/round-to-negative-infinity integer division (as opposed to the default round-to-zero).     7 floordiv 5 = 1     -3 floordiv 5 = -1     -6 floordiv 5 = -2 As I guess that doesn't exist, the operation can be constructed as:    (a/b) + (a>>31) Assuming a is 32 bits. I can

I am new to LLVM and couldn't find any llvm-user list, so I am posting my user question here, sorry. I am trying to create a simple "puts" call accepting the static string, with the code below. The last line (CallInst::Create) fails with an assert: "Calling a function with a bad signature!" Because the type of function is void(u8*) and the argument supplied is:

As I understand it,  predict.lm(l ,newdata=nd ,interval="confidence") yields confidence bands for the predicted mean of new observations and lm.predict(l ,newdata=nd ,interval="prediction") yields confidence bands for new observations themselves, given an lm object l.   However with regard to {mgcv} although  predict.gam (g ,se.fit=TRUE ,interval= "prediction")

I have an lme model that I want to use for prediction. With lm objects it is possible to use "interval" and "level" options of predict.lm to obtain prediction intervals. This seems not to be applicable for predict.lme. Is there a way to get prediction intervals also for lme predictions? Regards, Kari --

Hi, I know this is not exactly an R question but may be someone will nice enough to give me a pointer. I'm using nnet to fit a non linear univariate function. I wonder if there is a way to estimate a confidence interval for the predicted output beside using the residuals? The data set I use is relatively small and I use only a few (5:10) of these as test set or should I say validation set.

Hi, I'm regressing various body dimensions upon body mass using the 'lmodel2' function, as I'm keen to obtain both OLS and RMA slope values. I also wish to create a plot of the regressions, with the 95% confidence interval of both the slope and intercept. I know how to plot 95% ci bands of the OLS slope using lm with the 'predict' function and 'matlines'. Does

I am using R 2.3.0, Is there a way to get prediction intervals using predict.gls? Any ideas would be appreciated. thanks, Spencer On 11/2/06, Frank McCown <fmccown@cs.odu.edu> wrote: > > I was wondering if anyone knows who should be contacted to add to the R > user-contributed documentation at > > http://www.r-project.org/other-docs.html > > There doesn't

Hello everybody, when I create an object of class boot with the function tsboot() from the package boot and try to compute several types of confidence intervals with boot.ci("object of class boot created with tsboot") I obtain the warning message, that "BCa-intervals are not defined for time-series bootstraps". Does that hold in general? Or is it just not defined in

I'm using the plotmeans function to plot the means and 95% CI of my groups, however I also want to get the actual numbers of the CI, i.e. the upper and lower bounds. Is there anyway to get that information out of plotmeans? If not, is there an easy way to calculate the CIs? -- View this message in context: http://old.nabble.com/Confidence-intervals-tp26225647p26225647.html Sent from the R

fixed @ R-forge. New version should appear on CRAN soon. Thanks for the report! Torsten > > ---------- Forwarded message ---------- > Date: Sat, 3 Sep 2011 23:56:35 +0200 > From: Ulrich Halekoh <Ulrich.Halekoh at agrsci.dk> > To: "r-help at r-project.org" <r-help at r-project.org> > Subject: [R] glht (multcomp): NA's for confidence intervals using

Dear All, Is it possible to get confidence intervals for Harrell's concordance index or, equivalently, Somer's D using the rms package or in some other way ? I have survival data it would be the c-index in the Cox model setting Many thanks Dr Bernard North Statistical Consultant Statistical Advisory Service Advice and Courses on Research Design and Methodology Imperial College South

Hi, Sorry for repeated question. I performed logistic regression using lrm and penalized it with pentrace function. I wanted to get confidence intervals of odds ratio of each predictor and summary(MyModel) gave them. I also tried to get bootstrapping standard errors in the logistic regression. bootcov function in rms package provided them. Then, I found that the confidence intervals provided by

Is anyone aware of R code for calculating sample size in the context of tolerance intervals? Thanks, Keith [[alternative HTML version deleted]]

Hi, I have a question concerning color pallets. I am currently plotting geophysical fields with spplot (sp package) and I would like to create a pallet with open boundaries. For instance, I have a field whose values vary between -7 et 1, but a few values are much higher, for instance 28 or 32. As a result, I would like to create a palette with, for instance, 8 intervals within the range [-7,1]