similar to: overlapping confidence bands for predicted probabilities from a logistic model

Nella citazione martedì 2 agosto 2011 22:01:13, Carlo Alberto Ferraris ha scritto: > My question is: > what is the best way to > express such relationships in LLVM IR ("best" in the sense of allowing > other optimizations to run effectively)? Bear in mind that in this > example N=2, but it may be way bigger than that. Just to clarify: I already figured out two ways to

Dear friends of lme, After so many year with lme, I feel ashamed that I cannot get this to work. Maybe it's a syntax problem, but possibly a lack of understanding. We have growth curves of new dental bone that can well be modeled by a linear growth curve, for two different treatments and several subjects as random parameter. By definition, newbone is zero at t=0, so I tried to force the

Why is this a regalloc problem? I assume in the example below the "r0" is somehow forced by the ABI? Because otherwise moving the texture2d operation into the branch wouldn't matter as long as we assign different registers to the two branches and use a technique like lib/Target/R600/SIFixSGPRLiveRanges.cpp. - Matthias > On May 13, 2015, at 6:00 PM, Philip Reames <listmail at

Hi Jingyue, Convergent is not intended to prevent inlining. It’s tricky to formalize this inter-procedurally, but the intended interpretation is that a convergent operation cannot be move either into or out of a conditionally executed region. Normal inlining would not violate that. I would imagine that it would make sense to use a combination of convergent and noduplicate for barrier-like

Below is a proposal for a new "convergent" intrinsic attribute and MachineInstr property, needed for correctly modeling many SPMD/SIMT programming models in LLVM. Comments and feedback welcome. —Owen In order to make LLVM more suitable for programming models variously called SPMD and SIMT, we would like to propose a new intrinsic and MachineInstr annotation called

Hi Mehdi, My reading of it is that if you have a convergent instruction A, it is legal to duplicate it to instruction B if (assuming B is after A in program flow) A dominates B and B post-dominates A. James On Fri, 14 Aug 2015 at 08:32 Mehdi Amini via llvm-dev < llvm-dev at lists.llvm.org> wrote: > On Aug 13, 2015, at 9:43 PM, Owen Anderson via llvm-dev < > llvm-dev at

Nella citazione martedì 2 agosto 2011 20:02:08, Michael Ilseman ha scritto: > I'm assuming that you're talking about a situation where this can't be > determined statically in the existing LLVM IR, but you know it's true > and want to put it in (e.g. you're the one generating LLVM IR). Correct. Or, more precisely, I'd like to investigate macro compression, i.e.

Greetings all, I have two logistic plots coming from two calls to plogis. The code is .x <- seq(-7.6, 7.6, length=100) plot(.x, plogis(.x, location=0, scale=1), xlab="x", ylab="Density", main="Logistic Distribution: location = 0, scale = 1", type="l") abline(h=0, col="gray") .y <- seq(-7.6, 7.6, length=100) plot(.x, plogis(.x,

I added "plogis" to the derivative table in the development version of R; the patch against yesterday's R-devel src/deriv/main.c is available at http://www.zoology.ufl.edu/bolker/deriv_patch.txt . I pretty much followed the framework of the other symbols; here was my incantation - } else if (CAR(expr) == PlogisSymbol) { - ans = simplify(TimesSymbol, -

Hi, When running z <- plot(fit, age=NA, cholesterol=NA, perim=boundaries, method='image') Legend(z, fun=plogis, at=qlogis(c(.01,.05,.1,.2,.3,.4,.5)), zlab='Probability') And after pointing the cursor to the plot() screen in R, I obtain the following message: Using function "locator(2)" to place opposite corners of image.legend Error in

Hi all, Where f(x) is a logistic function, I have data that follow: g(x) = f(x)*.5 + .5 How would you suggest I modify the standard glm(..., family='binomial') function to fit this? Here's an example of a clearly ill-advised attempt to simply use the standard glm(..., family='binomial') approach: ######## # First generate some data ######## #define the scale and location of

dear£º in the example£¨nomogram£©£¬I don't understand the meanings of the program which have been marked by red line.And how to compile the program(L <- .4*(sex=='male') + .045*(age-50) + (log(cholesterol - 10)-5.2)*(-2*(sex=='female') + 2*(sex=='male'))). n <- 1000 # define sample size set.seed(17) # so can reproduce the results age <- rnorm(n, 50, 10)

Hi all R users I did a logistic regression with my binary variable Y (0/1) and 2 explanatory variables. Now I try to draw my nomogram with predictive value. I visited the help of R but I have problem to understand well the example. When I use glm fonction, I have a problem, thus I use lrm. My code is: modele<-lrm(Y~L+P,data=donnee) fun<- function(x) plogis(x-modele$coef[1]+modele$coef[2])

Dear all, I have a data frame f, with four variables: f <- data.frame(A=c(0,0,1,1), B=c(0,1,0,1), C=c(1,1,0,1), D=c(3,1,2,3)) f A B C D 1 0 0 1 3 2 0 1 1 1 3 1 0 0 2 4 1 1 1 3 I want to create a new variable (f$E), such that each of its elements is drawn from either f$A, f$B, or f$C, according to the value (for each row) of f$D (values of which range from 1 to 3). In the first row, D is

I am new to R and I am trying to do a monte carlo simulation where I generate data and interject error then test various cut points; however, my output was garbage (at x equal zero, I did not get .50) I am basically testing the performance of classifiers. Here is the code: n <- 1000; # Sample size fitglm <- function(sigma,tau){ x <- rnorm(n,0,sigma) intercept <- 0 beta

Dear all, ggplot currently requires 13 packages (grid, reshape, RColorBrewer, proto, splines, MASS, Hmisc, boot, butler, hexbin, mapproj, quantreg, sm). Some of these are absolutely necessary (eg. proto), but most are used for one or two specific tasks (eg. boot is only used to get plogis, used for logit scales). Do you think I should make them all "depends" packages, or

Hello colleagues, This is a follow up to a question I posed in November regarding an analysis I was working on. Thank you to Dr. Brian Ripley and Dr. John Fox for helping me out during that time. I am conducting logistic regression on data set on psi (ESP) ganzfeld trials. The response variable is binary (correct/incorrect), with a 25% guessing base rate. Dr. Ripley suggested that I

Hi there! Happy new year to everyone! There's a piece of code that I must write that's driving me crazy. Maybe any of you has previous experiences in something similar. Any help will be greatly appreciated! The problem is as follows. I have a matrix Z with dimensions c(m, p). I have two vectors Gamma and Th with length p. What I want to do is, for j in 1:p, for each pair

dear professor: I have a problem about the nomogram.I have got the result through analysing the dataset "exp2.sav" through multinominal logistic regression by SPSS 17.0. and I want to deveop the nomogram through R-Projject,just like this : > n<-100 > set.seed(10) > T.Grade<-factor(0:3,labels=c("G0", "G1", "G2","G3")) >

dear professor: thank you for your help,witn your help i develop the nomogram successfully. after that i want to do the internal validation to the model.i ues the bootpred to do it,and then i encounter problem again,just like that.(´íÎóÓÚerror to :complete.cases(x, y, wt) : ²»ÊÇËùÓеIJÎÊý¶¼Ò»Ñù³¤(the length of the augment was different)) i hope you tell me where is the mistake,and maybe i have