search for: cooks

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>

where is the cook-distance in R? i can't find it!please help me!

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) treatment <- gl(3,3) d.AD <- data.frame(treatment, outcome, counts) glm.D93 <- glm(counts ~ outcome + treatment, family=poisson()) opar <- par(m...

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. >>

...ia.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 > linmod$residuals[1]^2/(2*mean(linmod$residuals^2))*(hatvalues(linmod)[1]/(1-hatvalues(linmod)[1])^2) 1 0.02503195 > cooks.distance(linmod)[1] 1 0.02490679 Why differ the two results? Thanks a lot if somebody have some instructions for me. Best wishes: Kolos

...(2) i.e. has the weight in there. Apart from the division this is sum of weighted squares of differences yhat_j - yhat_j[i]. (That is, it is the weighted sum of squares of fits minus fits with ith point deleted.) However, a little experimentation in R, using ls.diag(fit)$cooks, suggests that in weighted case R gives (1) times some constant. Does anybody know how that constant is calculated? What is the rationale for using equation (1) (times a constant) in the weighted case anyway? Thanks. [[alternative HTML version deleted]]

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 <- if (isGlm) summary(x)$dispers...

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

...nd] labels.id <- labels.id[wind] } n <- length(r) if (any(show[2:5])) { s <- if (inherits(x, "rlm")) x$s else sqrt(deviance(x)/df.residual(x)) hii <- lm.influence(x, do.coef = FALSE)$hat if (any(show[4:5])) { cook <- if (isGlm)cooks.distance(x) else cooks.distance(x, sd = s, res = r) } } if (any(show[c(2:3,5)])) { ylab23 <- if (isGlm) "Std. deviance resid." else "Standardized residuals" r.w <- if (is.null(w)) r else sqrt(w) * r rs <- r.w/(s *...

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) > gl...

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, they are different, although the same model is calculated (the coefficients are the same etc.) It seems that different calculation-formulas are used for cooks.distance and dfbetas in SPSS compared...

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 !)

...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 for the same data, and sure enough the data with the indices grater than 250 (x axis) have obvious higher Cook ?s distance than the majority of the data. The data indices on the Cook?s distance plot are different than my data ID (in my data table) which is ?character type?. How do I id...

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

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" >

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

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 >>

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:

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:

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: