similar to: isotonic/ordered heterogeneity tests

Well, I could argue that it's not *completely* OT since my question is motivated by an enquiry that I received in respect of a CRAN package "Iso" that I wrote and maintain. The question is this: Given observations y_1, ..., y_n, what is the solution to the problem: minimise \sum_{i=1}^n (y_i - y_i^*)^2 with respect to y_1^*, ..., y_n^* subject to the "isotonic"

Hi, Has anyone written code for isotonic regression on ordered rectangular grids? Nathan Nathan Leon Pace, MD, MStat University of Utah Salt Lake City, UT 84132 Office: 801.581.6393 Fax: 801.581.4367 Cell: 801.558.3987 Pager: 801.291.9019 Home: 801.467.2925 [[alternative text/enriched version deleted]]

Dear R-users Do you know of an easy way in R of performing "isotonic (unimodal)" regression ala BBBB, Barlow, Bartolomew, Brenner and Brunk. best regards Helgi -- Helgi Tomasson FAX: 354-552-6806 University of Iceland PHONE:354-525-4571 Faculty of Economics and Business Administration email:helgito at

Fixes issue #95 on GitHub. --- src/opus_multistream_encoder.c | 57 ++++------------------------------ 1 file changed, 6 insertions(+), 51 deletions(-) diff --git a/src/opus_multistream_encoder.c b/src/opus_multistream_encoder.c index 6cc1f432..9cb9bf34 100644 --- a/src/opus_multistream_encoder.c +++ b/src/opus_multistream_encoder.c @@ -742,20 +742,9 @@ static void ambisonics_rate_allocation( {

Hi I'm trying to develop some C code to find the fixpoint of a contraction mapping, the code compiles and gives the right results when executed in R. However R-gui session is frequently terminated. I'm suspecting some access violation error due to the exception code 0xc0000005 In the error report windows 10 gives me. It is the first time I'm writing any C-code so I'm guessing I

Hello all, A really noddy question for you all: I''m trying without success to do some subhypothesis testing. Using simple anova model, with a toy dataset from a book. I have four factors A,B,C,D, and wish to test mu_C = mu_D. This is what I have tried: > contrasts(infants$group,how.many=1) <- c(0,0,1,-1) > contrasts(infants$group) [,1] A 0 B 0 C 1

My data have heterogeneity of variance (in a categorical variable), do I need to specify a variance structure accounting for this in my model or do GLMMs by their nature account for such heterogeneity (as a result of using deviances rather than variances)? And if I do need to do this, how do I do it (e.g. using something like the VarIdent function in nlme) and in what package? This is my first

Hi all, I have major heterogeneity in variances across labs (100-fold). There is no apparent variance heterogeneity across y-hat. By using lme4 in the following way, am I accounting for the variance differences in labs?: lmer(y ~ fixed1 + covariates + (fixed1|labs)) I'm not sure that it is - I think it is only allowing the means (slopes [conditional means] & intercepts) to differ

Dear list members, I am looking for an alternative function for a two-way ANOVA in the case of variance heterogeneity. For one-way ANOVA, I found oneway.test(), but I didn't find anything alike for two-way ANOVA. Does anyone have a suggestion? Thank you! Maike Luhmann Freie Universit?t Berlin

Hi All, I need some help with the package 'isotone'? I have a big matrix (long) and I want to apply 'lsSolver' possibly with 'activeSet' to each row of the matrix. The plan is to use function 'apply', I tried several ways, but didn't work. Not sure if the FUN is activeSet or lsSolver. If I use the loop, then it works, but very slow. for (i in 1:N) {

Hi, I am trying to add multiple variance structures such as the first example below: vf1 <- varComb(varIdent(form = ~1|Sex), varPower()) However my code below will not work can anybody please advise me? VFcomb<-varComb(varExp(form=~depcptwithextybf),varFixed(form=~FebNAO)) also if you have two variables with the same weights function would you write that as:

Classification: UNCLASSIFIED Caveats: NONE A similar question has been posted in the past but never answered. My question is this: for probit analysis, how do you program a 95% confidence interval for the LD50 (or LC50, ec50, etc.), including a heterogeneity factor as written about in "Probit Analysis" by Finney(1971)? The heterogeneity factor comes into play through the chi-squared

I have numerous replicated goodness-of-fit experiments (observed compared to expected counts in categories) and these replicates are nested within a factor. The expected counts in each cell are external (from a scientific model being tested). The calculations I need within each level of the nesting factor are a heterogeneity G test, with the total G and the pooled G across replicates. Then I

Dear All My data consists in 96 groups, each one with 10 observations. Levene's test suggests that the variances are not equal, and therefore I have tried to apply the classical transformations to have homocedasticity in order to be able to use ANOVA. Unfortunately, no transformation that I have used transforms my data into data with homocedasticity. The histogram of variances is at

Dear R-ians, I'm looking for a computational simplified formula to calculate a measure for heterogeneity (let's say H ): H = sqrt [ (Si (Sj (Xi - Xj)?? ) ) /n ] where: sqrt = square root Si = summation over i (= 0 to n) Sj = summation over j (= 0 to n) Xi = element of X with index i Xj = element of X with index j I can simplify the formula to: H = sqrt [ ( 2 * n * Si (Xi) - 2 Si (Sj

Hi! My question(s) in the end might be silly but I am no expert on this, so here it goes: Noy-Meir (1973), Pielou (1984) and a few others have pointed to non-centered PCA being in some cases useful. They clearly explain that "it is the case" when multi-dimensional data display distinct clusters (which have zero, or near-zero, projections in some subset of the axes) and the task is

Hello I am looking for a function to create an Integrated (I) spline basis, somehting similar to the likes of 'bs' and 'ns'. I have come across the funcitons, fda::eval.monfd Values of a Monotone Functional Data Object fda::/.fd FDA internal functions fda::monfn Evaluates a monotone function fda::smooth.monotone Monotone

Binary distributions of R-0.49 for NEXTSTEP (Intel and M68k) are now available on CRAN: http://www.ci.tuwien.ac.at/R/bin/i386-nextstep/R.0.49.I.b.tar.gz http://www.ci.tuwien.ac.at/R/bin/m68k-nextstep/R.0.49.N.b.tar.gz Because NEXTSTEP doesn't support dynamic loading, I've compiled in a number of additional functions (mostly from the user contributed section of CRAN) which I find

I think that users quite often want to answers to questions like ``Is there something to do FOO in R?'', where FOO might e.g. be ``isotonic regression''. The answer should be something like ``you can use BAR in package BAZ, or ...''. For this, full text search is not the right approach and the keywords are not enough. We could maybe search dedicated fields (like \title),

Hello, I'm interested in correcting for and measuring unobserved heterogeneity ("missing variables") using R. In particular, I'm searching for a simple way to measure the amount of unobserved heterogeneity remaining in a series of increasingly complex models (adding additional variables to each new model) on the same data. I have a static database of 400,000 or