similar to: Confidence intervel for regression line

Hi all, I am trying to plot the one-sided confidence limits for the regression line. It seems it is ok to use predict function to compute the two sided confidence limits. Does any one know a easy way to compute the one sided confidence limits? Thank you very much in advance. Hannah [[alternative HTML version deleted]]

Hi, I have a glm gives summary as follows, Estimate Std. Error z value Pr(>|z|) (Intercept) -2.03693352 1.449574526 -1.405194 0.159963578 A 0.01093048 0.006446256 1.695633 0.089955471 N 0.41060119 0.224860819 1.826024 0.067846690 S -0.20651005 0.067698863 -3.050421 0.002285206 then I use confint(k.glm)

Hello, I'm trying to fit some points with a 8-degrees polynom (result of lm is stored in pfit). In most of the case, it is ok but for some others, some coefficients are "NA". I don't really understand the meaning of these "NA". And the problem is that I can't perform a derivation (pderiv<-as.function((deriv(polynomial(pfit$coefficients))))) on pfit due to the

Hello, I probably have a syntax error in trying to generate an expected survival curve from a weighted cox model, but I can't see it. I used the help sample code to generate a weighted model, with the addition of a "weights=albumin" argument (I only chose albumin because it had no missing values, not because of any real relevance). Below are my code with the resulting error

Hello, I have 3 columns : a, b and a*b I would like to find the pair (a,b) so that a*b is the minimum but not from the points I measured but from the fit of the curve (I have more points that the ones given below but I fit only on this part because I know that the minimum a*b is in this interval). I thought doing it this way : - to fit a*b=f(a) abfit<-lm(ab ~ poly(a,8,raw=T)) - to use the

Hi I have the following formula (I hope it is clear - if no, I can try to do better the next time) h(x, a, b) = integral(0 to pi/2) ( ( integral(D/sin(alpha) to Inf) ( ( f(x, a, b) ) dx ) dalpha ) and I want to do an mle with it. I know how to use mle() and I also know about integrate(). My problem is to give the parameter values a and b to the

It is a complex function, functions are quoted frequently, you may read from bottom up The independent variable for final fit is q %%Rg0 is a function of L and b Rg0sq<-function(L,b)L*b/6*(1-3/2*b/L+3/2*(b/L)^2-3/4*(b/L)^3*(1-exp(-2*L/b))) %%alpha is a defined function alpha<-function(x)(1+(x/3.12)^2+(x/8.67)^3)^(0.176/3) %%w is a defined function

I'm applying logistic regression to a moderate sized data set for which I believe Wald based confidence intervals on B coefficients are too conservative. Some of the literature recommends using confidence intervals based on the likelihood ratio in such cases, but I'm having difficulty locating a package that can do these. Any help would be immensely appreciated. Best, Jeff Hanna --

I saw a similar question but I still don't fully understand how to implement optim. Can someone help me out with this? Thanks. Keun-Hyung > vol<-rep(c(0.03, 0.5, 2, 4, 8, 16, 32), 3) > time<-rep(c(2,4,8),each=7) > p.mated<-c(0.47, 0.48, 0.43, 0.43, 0.26, 0.23, "null", 0.68, 0.62, 0.64, 0.58, 0.53, 0.47, + 0.24, 0.8, 0.79, 0.71, 0.56, 0.74, 0.8, 0.47) >

This patch fixes two spelling mistakes in code comments, which means no functional change: still-extant -> still-existant the -> then Okay? Index: sshbuf.c =================================================================== RCS file: /cvs/src/usr.bin/ssh/sshbuf.c,v diff -u -p -u -p -r1.19 sshbuf.c --- sshbuf.c 2 Dec 2022 04:40:27 -0000 1.19 +++ sshbuf.c 13 Aug 2024 16:39:12 -0000 @@

Dear all, In order to be sure I understand glmm correctly, I try to reproduce by hand a simple result. Here is a reproducible code. The questions are in _________________ Of course I have tried to find the solution using internet but I was not able to find a solution. I have also tried to follow glmer but it is very complicated code! Thanks for any help. Marc # Generate set of df with nb

Hello List! We're having trouble making call deflection on ISDN PRI. We would like to transfer a call to an external extension but keeping the callerid of the caller so it can be presented to the receiver of the transferred call. At the time we're using Zaptel 1.4.5.1, Asterisk 1.4.11 and Digium hardware TE420B. We've ordered the service (CD) from the phone company. The

I'm interested in knowing if anyone else has worked around this issue: I have an application that needs to check the status of the calls going through Asterisk about every 5 seconds or so. I don't want to do "asterisk -rx 'show channels verbose'" at the Linux command line 12 times per minute so I am looking at the AMI. I see that there isn't a manager command

Hello R-list, I am trying to calculate a ridge regression using first the *lm.ridge()* function from the MASS package and then applying the obtained Hoerl Kennard Baldwin (HKB) estimator as a penalty scalar to the *ols()* function provided by Frank Harrell in his Design package. It looks like this: > rrk1<-lm.ridge(lnbcpc ~ lntex + lnbeerp + lnwinep + lntemp + pop, subset(aa,

Hi List! I got this error while upgrading zaptel: make -C firmware hotplug-install DESTDIR= make[1]: Entering directory `/usr/src/zaptel-1.4.7.1/firmware' Attempting to download zaptel-fw-oct6114-064-1.05.01.tar.gz --10:53:09-- http://downloads.digium.com/pub/telephony/firmware/releases/zaptel-fw-oct6114-064-1.05.01.tar.gz Resolving downloads.digium.com... failed: Temporary

Invitation accepted, I am happy to help out with reviews, like I did with the previous VP patches. And of course agreed that things should be well defined, and that we shouldn't paint ourselves in a corner, but I don't think that this is the case. And it's not that I am in a rush, but I don't think this change needs to be predicated on a big change landing first like the LV

Hi Simon, Thanks for reposting the example, and looking at it more carefully, I think it is very similar to my first proposal. This was met with some resistance here because it dumps loop information in the vector preheader. Doing it this early, we want to emit this in the vectoriser, puts a restriction on (future) optimisations that transform vector loops to honour/update/support this intrinsic

> You have similar problems with https://reviews.llvm.org/D79100 The new revision D79100<https://reviews.llvm.org/D79100> solves your comment 1), and I don't think your comments2) and 3) apply as there are no vendor specific intrinsics involved at all here. Just to quickly discuss the optimisation pipeline, D79100<https://reviews.llvm.org/D79100> is a small extension for the

On Tue, 13 Aug 2024, Tobias Stoeckmann wrote: > This patch fixes two spelling mistakes in code comments, > which means no functional change: > > still-extant -> still-existant extant is a valid word > the -> then ok

Hi Hanna, your function is essentially zero outside a short interval around 9. And the help page states: "If the function is approximately constant (in particular, zero) over nearly all its range it is possible that the result and error estimate may be seriously wrong." You could try to integrate over a finite interval, say (7, 12). G?ran Brostr?m On 2018-02-06 19:40, li li wrote: