similar to: *** GOODNESS OF FIT FOR BINOMIAL DISTRIBUTED DATA

Dear All, I run the goodness of fit test using goodfit() in vcd package. The result is as follow: Goodness-of-fit test for poisson distribution X^2 df P(> X^2) Pearson 1.053348 2 0.5905661 Warning message: In summary.goodfit(gf) : Chi-squared approximation may be incorrect I want to save the the test statistics(X^2), df, and p-value. How can I save the result.

Dear all, I am trying to estimate a system of equations with a Seemingly Unrelated Regression. However because of the characteristics of the data I'd like to do it with a negative binomial estimation. Would anybody know how to implement a Seemingly Unrelated Negative Binomial (SUNB) estimation in R? Thank you in advance for your help. Best regards, Elisa Lanzi -- Elisa Lanzi PhD student in

Hi, I'm using Vlans in my network as a way of preventing pier to pier communication - I only want nodes in the network to talk to the gateway (a linux box). I have successfully set up lots of sub interfaces using the vconfig too, one for each vlan. What I would like to be able to do is remove the ip address from each of these subinterfaces eth0.x and bridge them to eth0. I have successfully

[code]library(MASS) x=c(rep(0,8096), rep(1,1629), rep(2,233), rep(3,38), rep(4,4) ) x.bar=round(mean(x),4) x.var=round(var(x),4) p.hat=round(x.bar/x.var,4) alpha.hat=round(x.bar*p.hat/(1-p.hat),4) fitdistr(x, "Negative Binomial") fitdistr(x, "Poisson")[/code] 1- fitdistr(x, "Negative Binomial") the parameters got here,

Estimados miembros de la lista. Estoy usando 2 funciones del paquete vcd y obtengo resultados que parecen discrepar entre ambas funciones. > dput(peces) c(26L, 63L, 1L, 21L, 20L, 50L, 0L, 104L, 19L, 0L, 8L, 32L, 0L, 24L, 5L, 2L, 0L, 36L, 0L, 5L, 27L, 1L, 13L, 24L, 15L, 25L, 23L, 5L, 37L, 26L, 29L, 14L, 15L) La función Ord_plot me dice que la mejor distribución para los datos es binomial

Hi All, I have a dataset consisting of abundance counts of a fish and I want to test if my data are poisson in distribution or normal. My first question is whether it is more appropriate to model my data according to a poisson distribution (if my test says it conforms) or use transformed data to normalise the data distribution? I have been using the vcd package gf<-goodfit(Y,type=

Hi All: This is really getting into the weeds, but I am hoping someone will have a solution. I am trying to use dygrahs for R, within Shiny. The situation arises when I am combining a number of dygraphs into one plot. If I am just in an RNotebook, if you look at: https://stackoverflow.com/questions/30509866/for-loop-over-dygraph-does-not-work-in-r the solution to have the plot shown from a

Hello, Sample code: library("vcd") dummy <- rnbinom(200, size=1.5, prob=0.8) gf <- goodfit(dummy, type="nbinomial", method="MinChisq") plot(gf) I would like to: 1. add a lgened stating the bars show the actual counts and the red dots - the fit. 2. show the goodness-of-fit values calculated somewhere on an empty white space ob the plot. But... the legend

Hello, I am a student and for project I need R. I have one problem regarding function goodfit(). Does goodfit() require frequency count of numbers or numbers themselves? For example suppose I have data say 150 readings.Do I need to use goodfit() directly on data or should I make suitable no of bins and then apply goodfit()? Aswad [[alternative HTML version deleted]]

Dear R-Help: As you can see, Prof. Friendly refers me to your site for an executable version of vcd. I don't mean to be obtuse, but 15 minutes spent exploring your site failed to locate a downloadable version of the vcd package to which he referred. I know plainly what this application can do. What I need to know is how to obtain the application itself. My thanks in advance for any

I have troubles understanding how goodfit() function in the vcd package computes the Pearson coefficient. Can anybody provide more information on the computation? In particular, for HorseKicks data in vcd package, goodfit() yields > oo <- goodfit(HorseKicks,type="poisson",method="MinChisq") > summary(oo) Goodness-of-fit test for poisson distribution

Try changing your method to "ML" and try again. I tried the run the first example from the documentation and it failed with the same error. Changing the estimation method to ML worked. @List: Can anyone else verify the error I got? I literally ran the following two lines interactively from the example for goodfit: dummy <- rnbinom(200, size = 1.5, prob = 0.8) gf <- goodfit(dummy,

Hey, Does anyone know if there is a way to get back from goodfit what it estimated the parameters to be? I used the code fit<-goodfit(round(data$PLX_NRX),type="nbinomial" and got a pretty good fit. I could not however duplicate this good fit with any parameter estimates that I had. Any ideas??? Thanks, Elizabeth Lawson ---------------------------------

Hi, I'm trying to use rsync to backup a linux filesystem to a windows server. I followed the hints that I found at http://www.tiarnan.phlegethon.org/rsyncntdoc.html to run rsync on windows, and it works quite well. The only problem I found is that windows is not able to backup linux special files (/dev/*). I don't know if the problem is in the way rsync has been compiled, or simply in

Hi, is there any method for goodness of fit testing of an (as general as possible) univariate distribution with parameters estimated, for normal, exponential, gamma distributions, say (e.g. the corrected p-values for the Kolmogorov-Smirnov or Chi-squared with corresponding ML estimation method)? It seems that neither ks.test nor chisq.test handle estimated parameters. I am aware of function

Hi. I'm pretty new to ocfs2 and clusters. I'm trying to make ocfs2 running over a drbd device. I know it's not the best solution but for now i must deal with this. I set up drbd and work perfectly. I set up ocfs and i'm not able to make it to work. /etc/init.d/o2cb status: Module "configfs": Loaded Filesystem "configfs": Mounted Module

Dear r list,   I am using glm.nb in the MASS package to fit negative binomial models to data on manta ray abundance, and AICctab in the bbmle package to compare model IC.  However, I need to test for the goodness of fit of the full model, and have not been able to find a Pearson's Chi Squared statistic in any of the output.  Am I missing it somewhere?  Is there a way to run the test using

I'm trying to enter a frequency table manually so that I can run a goodness of fit test (I only have the frequencies, I don't have the raw data). So for example, let's say I want to re-create the HorseKicks table: library(vcd) data(HorseKicks) str(HorseKicks) 'table' int [1:5(1d)] 109 65 22 3 1 - attr(*, "dimnames")=List of 1 ..$ nDeaths: chr [1:5]

Hi, I have a problem of loss of file ownership with rsync. For some odd reasons, I have to use a windows machine as rsync server, and to backup/restore a filesystem from/to a linux client. All files in my linux filesystem are owned by root, with gid root. If I save the files onto the windows rsync server from linux using rsync, and then restore them back to linux, the ownership for all files

Hi, Back in 2011, it was reported that Liebert PSA devices persist in reporting OB (On Battery) when using usbhid-ups regardless of the actual state. Pier Paolo did some work (2011) which reportedly solved the issue. However, that doesn't seem to have reached mainstream and I now face the same problem. I'm using NUT 2.6.3 with a new Liebert PSA 1500Va that only ever reports OB and