search for: monotonicity

Hi all, I'm looking for smooth monotone estimation packages, preferably using splines. I downloaded the 'cobs' package and intend to use it, but since it offers only quadratic splines based on L1 minimization, I'd like to compare its performance to that of a more 'mainstream' cubic-spline, L2-norm minimizing spline. Preferably a smoothing spline. Does anyone know of such

Hi all, The C++11 (& C11) compare_exchange functions with explicit memory order allow you to specify two sets of semantics, one for when the exchange actually happens and one for when it fails. Unfortunately, at the moment the LLVM IR "cmpxchg" instruction only has one ordering, which means we get sub-optimal codegen. This probably affects all architectures which use

On Mon, Aug 22, 2011 at 9:55 AM, Jianzhou Zhao <jianzhou at seas.upenn.edu> wrote: > In the definition of 'monotonic' ordering, > ... "If an address is written monotonically by one thread, and other > threads monotonically read that address repeatedly, the other threads > must eventually see the write"... It's supposed to mean that if you have a something

On Mon, Aug 22, 2011 at 11:17 AM, Jianzhou Zhao <jianzhou at seas.upenn.edu> wrote: > On Mon, Aug 22, 2011 at 1:02 PM, Eli Friedman <eli.friedman at gmail.com> wrote: >> On Mon, Aug 22, 2011 at 9:55 AM, Jianzhou Zhao <jianzhou at seas.upenn.edu> wrote: >>> In the definition of 'monotonic' ordering, >>> ... "If an address is written

In the definition of 'monotonic' ordering, ... "If an address is written monotonically by one thread, and other threads monotonically read that address repeatedly, the other threads must eventually see the write"... Does this mean if a thread does multi-writes monotonically, monotonic reads from other threads should see all of them? But intuitively, it seems to be fine for a

Hi All, I am reading about LLVM IR atomics (http://llvm.org/docs/Atomics.html) and get confused about the difference between "Unordered" and "Monotonic". In particular, I am not sure I understand the statement of "It essentially guarantees that if you take all the operations affecting a specific address, a consistent ordering exists.". For me, it means that for the

On Mon, Aug 22, 2011 at 1:02 PM, Eli Friedman <eli.friedman at gmail.com> wrote: > On Mon, Aug 22, 2011 at 9:55 AM, Jianzhou Zhao <jianzhou at seas.upenn.edu> wrote: >> In the definition of 'monotonic' ordering, >> ... "If an address is written monotonically by one thread, and other >> threads monotonically read that address repeatedly, the other

Hi, I'm trying to find an implementation of monotonic regression in R and I haven't been able to find anything that's really related to this. isoMDS in the MASS package uses monotonic regression, however, I was wondering if there is any standalone function for monotonic regression? Basically what I'm trying to do is implement monotonic regression where I can see not just the

Here is a problem that perhaps someone out here has an idea about. It vaguely reminds me of something I've seen before, but can't place. Can anyone help? For multiple imputation, there are simpler methods available if the patterns of missing data are 'monotone' --- if Vj is missing then all variables Vk, k>j are also missing, vs. more complex methods required when the

On Mon, Aug 22, 2011 at 3:02 PM, Eli Friedman <eli.friedman at gmail.com> wrote: > On Mon, Aug 22, 2011 at 11:17 AM, Jianzhou Zhao <jianzhou at seas.upenn.edu> wrote: >> On Mon, Aug 22, 2011 at 1:02 PM, Eli Friedman <eli.friedman at gmail.com> wrote: >>> On Mon, Aug 22, 2011 at 9:55 AM, Jianzhou Zhao <jianzhou at seas.upenn.edu> wrote: >>>> In

Hi, I am trying to use R to mimic what I did in SAS. proc transreg data=x ; model identity(GSI)=monotone(group1); output out=d2 pprefix=M; run; Accroding to SAS documentation, the MONOTONE transfomation algorithm comes from (Kruskal 1964, secondary approach to ties). I have tried ace. it does provide some kind of monotone transformation, but it is not what I expected. Here is how

Hi, In my version of R, the stats package splinefun code for fitting a Fritsch and Carlson monotonic spline does not appear to guarantee a monotonic result. If two adjoining sections both have over/undershoot the way the resulting adjustment of alpha and beta is performed can give modified values which still do not satisfy the required constraints. I do not think this is due to finite precision

>I am trying to use the Hmisc function transace to transform predictors > > test<-cbind(flowstress,pressres,alloy) > xtrans<-transace(x,binary=pressres',monotonic='flowstress', categorical='alloy') > > >and I am getting the following message?? >Error in ace(x[, -i], x[, i], monotone = im, categorical = ic) : > unused argument(s) (monotone ...)

On Mon, Aug 22, 2011 at 3:02 PM, Eli Friedman <eli.friedman at gmail.com> wrote: > On Mon, Aug 22, 2011 at 11:17 AM, Jianzhou Zhao <jianzhou at seas.upenn.edu> wrote: >> On Mon, Aug 22, 2011 at 1:02 PM, Eli Friedman <eli.friedman at gmail.com> wrote: >>> On Mon, Aug 22, 2011 at 9:55 AM, Jianzhou Zhao <jianzhou at seas.upenn.edu> wrote: >>>> In

...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 Smoothing of Data mgcv::mono.con Monotonicity constraints for a cubic regression spline splines::backSpline Monotone Inverse Spline stats::isoreg Isotonic / Monotone Regression but none of these are specifically for an I-spline. Any help would be much appreciated. Helen Powell (Glsagow)

> On Apr 18, 2016, at 9:12 AM, Tom Stellard via llvm-dev <llvm-dev at lists.llvm.org> wrote: > > Here is the initial proposal with some formatting fixed: > > Currently, the LLVM IR uses a binary value (SingleThread/CrossThread) to > represent synchronization scope on atomic instructions. We would like to > enhance the representation of memory scopes in LLVM IR to allow

...s in the model. All this would be a perfect job for ANOVA except for one additional requirement: all factors are ordered, i.e. for any two levels in a factor one is bigger than the other, and I want the regression to preserve the ordering, that is to be monotonic. I can think of two definitions of monotonicity, weak and strong, and in case it matters I am more interested in the strong one, which I define as follows: If L1 < L2 within some factor F than prediction(L1, other factors) < prediction(L2, other factors) for ANY SELECTION of 'other factors' levels. (A weak monotonicity could be def...

...= y, b = double(nx), c = double(nx), d = double(nx), e = double(if (method == 1) nx else 0), PACKAGE = "stats") z$y <- z$y-z$x*gulim # trick to impose upper z$b <- z$b-gulim # limit on interpolator gradient z <- hyman.filter(z) # filter gradients for co-monotonicity z$y <- z$y+z$x*gulim # undo trick z$b <- z$b+gulim # transformation z <- spl.coef.conv(z) # force other coefficients to consistency u <- seq(xmin, xmax, length.out = n) .C("spline_eval", z$method, nu = length(u), x = u, y = double(n), z$n, z$x...

Has anyone got a function for smooth monotonic interpolation of a univariate function? I'm after something like the NAG function PCHIM which does monotonic Hermite interpolation. Alternatively, montononic cubic spline interpolation. Please reply directly. Rob Hyndman ___________________________________________________ Rob J Hyndman Associate Professor & Director of Consulting

Could anyone help me to find the mathematical expression to calculate the monotonicity correlation coefficient between two variables? Thanks in advance. Luis Rivera. Universidad de Alcal?. -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help&quo...