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2019 May 14
2
weakforced and GeoIP lookups
Hi Tobi, it should just work, but depends on the OS version. ./configure ?help tells you all the configure options, including: --with-maxminddb-includedir path to maxminddb include directory [default=auto] --with-maxminddb-libdir path to maxminddb library directory [default=auto] Neil > On 14 May 2019, at 17:44, Tobi via dovecot <dovecot at dovecot.org>
2003 Jun 04
3
cook distance
where is the cook-distance in R? i can't find it!please help me!
2006 Oct 24
1
Cook's Distance in GLM (PR#9316)
Hi Community, I'm trying to reconcile Cook's Distances computed in glm. The following snippet of code shows that the Cook's Distances contours on the plot of Residuals v Leverage do not seem to be the same as the values produced by cooks.distance() or in the Cook's Distance against observation number plot. counts <- c(18,17,15,20,10,20,25,13,12) outcome <- gl(3,1,9)
2019 May 14
2
weakforced and GeoIP lookups
Hi Tobi, This looks like you haven?t included the libmaxmind libraries before running configure. GeoIP support is only compiled in if it finds the right libs. This would be libmaxminddb-dev on Ubuntu for example. Neil >> Hi list >> >> hope it's okay to ask weakforced questions here as well, but I could not >> find a dedicated mailinglist for wforce. >>
2013 Mar 12
1
Cook's distance
Dear useRs, I have some trouble with the calculation of Cook's distance in R. The formula for Cook's distance can be found for example here: http://en.wikipedia.org/wiki/Cook%27s_distance I tried to apply it in R: > y <- (1:400)^2 > x <- 1:100 > lm(y~x) -> linmod # just for the sake of a simple example >
2005 Feb 11
1
cook's distance in weighted regression
I have a puzzle as to how R is computing Cook's distance in weighted linear regression. In this case cook's distance should be given not as in OLS case by h_ii*r_i^2/(1-hii)^2 divided by k*s^2 (1) (where r is plain unadjusted residual, k is number of parameters in model, etc. ) but rather by w_ii*h_ii*r_i^2/(1-hii)^2 divided by k*s^2,
2008 May 09
0
Incorrect fix for PR#9316: Cook's Distance & plot.lm
Bug PR#9316 noted an inconsistency between the Cook's distance contours on plot.lm(x, which = 5) and the values given by cooks.distance(x) -- as shown in plot.lm(x, which = 4) -- for glms: http://bugs.r-project.org/cgi-bin/R/Analyses-fixed?id=9316;user=guest;selectid=9316 The suggested fix was to modify the contour levels by a dispersion factor, implemented as follows: dispersion <-
2009 Feb 17
1
plot.lm: "Cook's distance" label can overplot point labels
The following code demonstrates an annoyance with plot.lm(): library(DAAGxtras) x11(width=3.75, height=4) nihills.lm <- lm(log(time) ~ log(dist) + log(climb), data = nihills) plot(nihills.lm, which=5) OR try the following xy <- data.frame(x=c(3,1:5), y=c(-2, 1:5)) plot(lm(y ~ x, data=xy), which=5) The "Cook's distance" text overplots the label for the point with the
2005 Apr 23
3
Enhanced version of plot.lm()
I propose the following enhancements and changes to plot.lm(), the most important of which is the addition of a Residuals vs Leverage plot. (1) A residual versus leverage plot has been added, available by specifying which = 5, and not included as one of the default plots. Contours of Cook's distance are included, by default at values of 0.5 and 1.0. The labeled points, if any, are those
2004 Mar 23
1
influence.measures, cooks.distance, and glm
Dear list, I've noticed that influence.measures and cooks.distance gives different results for non-gaussian GLMs. For example, using R-1.9.0 alpha (2003-03-17) under Windows: > ## Dobson (1990) Page 93: Randomized Controlled Trial : > counts <- c(18,17,15,20,10,20,25,13,12) > outcome <- gl(3,1,9) > treatment <- gl(3,3) > glm.D93 <- glm(counts ~ outcome +
2011 Apr 29
1
logistic regression with glm: cooks distance and dfbetas are different compared to SPSS output
Hi there, I have the problem, that I'm not able to reproduce the SPSS residual statistics (dfbeta and cook's distance) with a simple binary logistic regression model obtained in R via the glm-function. I tried the following: fit <- glm(y ~ x1 + x2 + x3, data, family=binomial) cooks.distance(fit) dfbetas(fit) When i compare the returned values with the values that I get in SPSS,
2001 May 25
1
Cook-Weisberg confidence curves
Is there an existing function to compute Cook-Weisberg confidence curves for non-linear model parameters in R? Kari Ruohonen -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !)
2003 Sep 03
1
plot only partial plots
Hi everybody, I would like to plot only a part of a data frame, and identify the IDs for all the points with values higher than a certain value. I will try to be more explicit: I did a qqnorm plot of my data. It is obvious from the plot that all the sample quantiles which are in Theoretical Quantiles = or > than 1 belong to another group. To be sure about that I plot the cooks.distance
2003 Aug 28
4
Cook-distance-type plot (vertical bars)
Hi, Figure 13 of Emmanuel Paradis's "R for Beginners" was produced by termplot working on an aov object. The lower right-hand plot is labelled "Cook's distance plot", and I'd really like to produce a similar type of figure, but in a totally different context. (I'm not even sure what this kind of figure is called, perhaps an "impulse plot", where
2016 Feb 19
4
should `data` respect default.stringsAsFactors()?
Hi Peter, Sorry if I was not clear. Perhaps an example will make my point: > data(iris) > class(iris$Species) [1] "factor" > write.table(iris,'data/myiris.tab') > data(myiris) > class(myiris$Species) [1] "factor" > rm(myiris) > options(stringsAsFactors = FALSE) > data(myiris) > class(myiris$Species) [1] "factor" >
2016 Feb 19
2
should `data` respect default.stringsAsFactors()?
Aha... Hadn't noticed that stringsAsFactors only works via as.is in read.table. Yes, the doc should probably be fixed. The code probably not -- packages loading different data sets depending on user options is an even worse idea than hav?ng the option in the first place... (I don't mean having the possibility, I mean the default.stringsAsFactor thing). In general, read.table() gets
2012 Oct 17
1
[LLVMdev] Howto Guide on Porting the LLVM Assembler
Yes, please do. Simon On Wed 17 Oct 2012 02:20:17 BST, Sean Silva wrote: > Wow this is awesome! Would it be okay if we linked to this from llvm.org/docs? > > -- Sean Silva > > On Tue, Oct 16, 2012 at 5:55 PM, Simon Cook <simon.cook at embecosm.com> wrote: >> Hi Everyone, >> >> I have been implementing the integrated assembler for the OpenRISC 1000 >>
2023 Oct 05
1
[PATCH 0/9] drm: Annotate structs with __counted_by
Am 02.10.23 um 20:22 schrieb Kees Cook: > On Mon, Oct 02, 2023 at 08:11:41PM +0200, Christian K?nig wrote: >> Am 02.10.23 um 20:08 schrieb Kees Cook: >>> On Mon, Oct 02, 2023 at 08:01:57PM +0200, Christian K?nig wrote: >>>> Am 02.10.23 um 18:53 schrieb Kees Cook: >>>>> On Mon, Oct 02, 2023 at 11:06:19AM -0400, Alex Deucher wrote:
2023 Oct 05
1
[PATCH 0/9] drm: Annotate structs with __counted_by
Am 02.10.23 um 20:22 schrieb Kees Cook: > On Mon, Oct 02, 2023 at 08:11:41PM +0200, Christian K?nig wrote: >> Am 02.10.23 um 20:08 schrieb Kees Cook: >>> On Mon, Oct 02, 2023 at 08:01:57PM +0200, Christian K?nig wrote: >>>> Am 02.10.23 um 18:53 schrieb Kees Cook: >>>>> On Mon, Oct 02, 2023 at 11:06:19AM -0400, Alex Deucher wrote:
2023 Oct 05
1
[PATCH 0/9] drm: Annotate structs with __counted_by
Am 02.10.23 um 20:22 schrieb Kees Cook: > On Mon, Oct 02, 2023 at 08:11:41PM +0200, Christian K?nig wrote: >> Am 02.10.23 um 20:08 schrieb Kees Cook: >>> On Mon, Oct 02, 2023 at 08:01:57PM +0200, Christian K?nig wrote: >>>> Am 02.10.23 um 18:53 schrieb Kees Cook: >>>>> On Mon, Oct 02, 2023 at 11:06:19AM -0400, Alex Deucher wrote: