similar to: Graphic Dispersion - Colored Points

Hi listers, Does it necessary to install any package in order to use the GINI or INEQ functions. If I use the following command the R tells me that didn't find the GINI function. x<-c(541, 1463, 2445, 3438, 4437, 5401, 6392, 8304, 11904, 22261) G<-gini(x) Thanks in advance, Marcio -- View this message in context:

Hi listers, I have the following code... data<-as.matrix(c(1,2,3,4,5,6,7,8,9,10),nrow=10,ncol=1,byrow=TRUE) n<-nrow(data) m<-n-1 boot<-data[sample(m,replace=T),] So, I need to count the number of times each observation was selected at the sample with replacement... Suppose I sampled... 4 5 1 3 7 5 1 4 7 So, I would count... x count 1 2 2 0 3 1 4 2 5 2 6 0 7 2 8 0 9 0 10 0

Hey listers, I am trying to do something simple... Check the program below... I would like to create a variable named COLOR according to the conditions that I stablished... But the problem is that it seems that my variable COLOR is checking just on sample, may be last in the loop... Certainly, I am missing something... Thanks in advance, Marcio

Hi listers, I have a simple doubt... I need to manipulate the data base as: var1 var2 7 0.1 7 0.1 8 0.12 10 0.15 12 0.18 20 0.31 I would like to aggregate the equal cases as var1 making the sum of var2... I would get... var1 var2 7 0.2 8 0.12 10 0.15 12 0.18 20 0.31 Thanks in advance, Marcio -- View this message in context:

Hey listers, I've posted this doubt other day... But I am still having a hard time... I have a MAC and I am not getting how to use the read.table command... At the bottom of the FINDER application I have the following path: Macintosh HD>Usu?rios>User>Marcio>UdeM>Travail Dirig?>Data>MU284 Population.txt I didn't find out how I could copy and paste this path as it is

Hi listers, I have a data frame with 5 variables... And I want reorder the data frame according a specific variable X... I checked the sort and order functions... In my case I think that the ORDER function is applicable... But I did not understand at all... The idea is simple... Data order by X... I know that this is very simple... Anyways... How I would do that... Thanks in advance, Marcio --

Hello, somebody can explain how to create dispersion graphic, because i need to put this dispersion graphics inside a matrix. The data is the next one: 2 test (mechanics and vector) open book. 3 test (algebra, analysis y statistics) closed book. Also could you explain which is the use of scor(bootstrap) And how can be used for create a matrix of graphics? Thanks, Tania [[alternative

Hi listers, If I would like to check if a variable contains certain value, I would write: if (10 %in% x) And If I would like to check the opposite, that 10 is not into x. How would be? Thanks in advance, Marcio -- View this message in context: http://r.789695.n4.nabble.com/Condition-in-tp2538110p2538110.html Sent from the R help mailing list archive at Nabble.com.

Hello, Which would be the command to change the size of the legend. I checked at the help and I found out something about TEXT.WIDTH, but I am not sure if is what I want. Any help! Thanks in advance, Marcio -- View this message in context: http://r.789695.n4.nabble.com/Size-of-the-legend-tp2547601p2547601.html Sent from the R help mailing list archive at Nabble.com.

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

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] =

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

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

I have been unsuccessful in extracting the dispersion parameter in SPLUS 6.1 using summary or summary.glm(modelobj$dispersion) from a glm object in which the family was set to quasi. This is the syntax given in the manual. I want to write a script to bootstrap the estimate of the dispersion parameter, but cannot seem to access that value. Any suggestions? Thanks, Ed ----------

Following p.206 of "Statistical Models in S", I wish to change the code for summary.glm() so that it estimates the dispersion for binomial & poisson models when the parameter dispersion is set to zero. The following changes [insertion of ||dispersion==0 at one point; and !is.null(dispersion) at another] will do the trick: "summary.glm" <- function(object, dispersion =

Dear R users, I would like to fit a glm with Poisson distribution and log link with a known dispersion parameter. I do not want to estimate the dispersion parameter. I know what it is, so I simply want to fix it at a constant for this and other models to follow. My simple, no covariate model is: Tall.glm<-glm(Seedling~1, family=poisson, offset(log(area)), data=tallPSME.df) I want to

I have been implementing a proposal of Jim Lindsey for glm(.) to return AIC values, and print.glm(.) and print.summary.glm(.) printing them.... however: >>>>> "Jim" == Jim Lindsey <jlindsey@luc.ac.be> writes: Jim> The problem still remains of getting the correct AIC when the user Jim> wants the scale parameter to be fixed. (The calculation should

I am running a binomial glm with response variable the no of mites of two species y->cbind(mitea,miteb) against two continuous variables (temperature and predatory mites) - see below. My model shows overdispersion as the residual deviance is 48.81 on 5 degrees of freedom. If I use quasibinomial to account for overdispersion the dispersion parameter estimate is 2501139, which seems

Three related questions on LMEs and GLMMs in R: (1) Is there a way to fix the dispersion parameter (at 1) in either glmmPQL (MASS) or GLMM (lme4)? Note: lme does not let you fix any variances in advance (presumably because it wants to "profile out" an overall sigma^2 parameter) and glmmPQL repeatedly calls lme, so I couldn't see how glmmPQL would be able to fix the dispersion