similar to: Dispersion Index in POT

Dear All, Could?someone please suggest me the way to calculate the optimal threshold in POT method via?any available ?packages in R? Thanks, Fir

Hi list I'm looking for statisitic measurements describing the pattern of points within a given polygon. Is there a function calculating the Index of Dispersion and/or are there other functions summarising an observed pattern? Markus Schwarz ..................................................................... Markus Schwarz Wissenschaftliche Mitarbeiterin Eidg. Forschungsanstalt WSL

Hello, I?ve got a statistical problem that I hope you can help me with. It doesn?t have to do directly with R, so if there?s another forum which would suit better, please tell me! Now here?s the problem: I want to derive confidence intervals for a variable X, which is - given the descriptive statistics - obviously negatively skewed and leptokurtic (i.e. peaked). My aim is to make a statement

Hi, I'd like to hear your opinion about the following proposal to make the computation of dispersion in GLMs more flexible. Dispersion is used in summary.glm; the relevant code chunk with the dispersion calculation is listed below (from glm.R): summary.glm <- function(object, dispersion = NULL, correlation = FALSE, symbolic.cor = FALSE, ...) { est.disp <- FALSE df.r <-

--Multipart_Wed_Feb__4_12:25:40_1998-1 Content-Type: text/plain; charset=US-ASCII Jim, I am relating your message to R-devel. This should be discussed in a broader audience; I am not an expert on GLM's, I know you are and others on this group also... R-develers, please CC to Jim Lindsey (on this topic), since he hasn't been part of the R-devel list for a while.. BTW: I will be gone

Dear experts, I tried to learn about Box-Cox-transformation but found the following thing: When I had to add a constant to make all values of the original variable positive, I found that the lambda estimates (box.cox.powers-function) differed dramatically depending on the specific constant chosen. In addition, the correlation between the transformed variable and the original were not 1 (as I

On Thursday 05 December 2013 15:53:58 Richard W.M. Jones wrote: > On Thu, Dec 05, 2013 at 04:30:05PM +0100, Pino Toscano wrote: > > Fix the dependencies of the libguestfs.pot target: other than using > > the right make variables holding the contents of the POTFILES, > > depend also on the POTFILES themselves. > > --- > > > > po/Makefile.am | 2 +- > >

Thank you for your reply. I am aware of the good reasons not to use the deviance estimate in binomial, Poisson, and gamma families. However, for the inverse Gaussian, the choice seems to me less clear cut. So I just wanted to compare two different options. I have used the dispersion parameter to compute the standardized deviance residuals: summary(model.gamma)$deviance.resid

I'm confused as to the trustworthiness of the dispersion parameters reported by glm. Any help or advice would be greatly appreciated. Context: I'm interested in using a fitted GLM to make some predictions. Along with the predicted values, I'd also like to have estimates of variance for each of those predictions. For a Gamma-family model, I believe this can be done as Var[y] =

Hello, I am currently working with the betareg package, which allows the fitting of a variable dispersion beta regression model (Simas et al. 2010, Computational Statistics & Data Analysis). I was wondering whether there is any package in R that allows me to fit variable dispersion parameters in the standard logistic regression model, that is to make the dispersion parameter contingent upon

Hi All, could someone shed some light on what the difference between the estimated dispersion parameter that is supplied with the GLM function and the one that the 'gamma.dispersion( )' function in the MASS library gives? And is there consensus for which estimated value to use? It seems that the dispersion parameter that comes with the summary command for a GLM with a Gamma dist. is

Greetings, I'm posting this OT query here because of out very international membership! In the French sentence "Les taux de tirage sont calcul??s de mani??re ?? ce que la dispersion soit inf??rieure ?? 5 % dans chaque strate." it would seem intended that the "dispersion" is to be calculated in a specific way (unstated) -- otherwise, how to ensure that it shall be

Hi, I would like to obtain the dispersion parameter for a quasipoisson model for later use in calculating QAIC values for model comparison.Can anyone suggest a method of how to go about doing this? The idea I have now is that I could use the residual deviance divided by the residual degrees of freedom to obtain the dispersion parameter. The residual deviance is available in the summary

On Thu, Dec 05, 2013 at 07:02:28PM +0100, Pino Toscano wrote: > On Thursday 05 December 2013 15:53:58 Richard W.M. Jones wrote: > > On Thu, Dec 05, 2013 at 04:30:05PM +0100, Pino Toscano wrote: > > > Fix the dependencies of the libguestfs.pot target: other than using > > > the right make variables holding the contents of the POTFILES, > > > depend also on the

Fix the dependencies of the libguestfs.pot target: other than using the right make variables holding the contents of the POTFILES, depend also on the POTFILES themselves. --- po/Makefile.am | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/po/Makefile.am b/po/Makefile.am index b0a8038..a8343ec 100644 --- a/po/Makefile.am +++ b/po/Makefile.am @@ -65,7 +65,7 @@ XGETTEXT_ARGS = \

Dear All, I was looking for the color index in?image function,?such as from topo.colors(n) and etc. but still never found it. For instance, from the help menu. ########################################### # Volcano data visualized as matrix. Need to transpose and flip # matrix horizontally. image(t(volcano)[ncol(volcano):1,]) # A prettier display of the volcano x <- 10*(1:nrow(volcano)) y

On Fri, Oct 02, 2015 at 01:31:30PM +0200, Pino Toscano wrote: > On Friday 02 October 2015 12:19:16 Richard W.M. Jones wrote: > > On Fri, Oct 02, 2015 at 11:48:46AM +0200, Pino Toscano wrote: > > > Traverse the po-docs directory before the subdirectories with translated > > > documentations, so we can make sure that libguestfs-docs.pot and the > > > translated

Using R 1.8.1, and the negative binomial glm implemented in MASS, the default when using anova and a chi-square test is to divide the deviance by the estimated dispersion. Using my UNIX version of S-plus (v 3.4), and the same MASS functions, the deviances are *not* divided by the estimated dispersion. Firstly, I'm wondering if anyone can enlighten about the correct procedure (I thought

Hi, I'm programming in R and below is a summary of a generalized linear model: ************************************************** *** Call: glm(formula = offspring ~ degdays, family = quasi(link = "log", variance = "mu"), data = fecundity) Deviance Residuals: Min 1Q Median 3Q Max -0.76674 -0.29117 -0.09664 0.15668 1.00800 Coefficients: Estimate Std. Error t value

> Hello, > > I have a question about a discrepancy between the > reported F statistics using anova() and add1() from > adding an additional term to form nested models. > > I found and old posting related to anova() and > drop1() regarding a glm with a dispersion parameter. > > The posting is very old (May 2000, R 1.1.0). > The old posting is located here. >