similar to: Std Err on Concentration measures

Hi, after looking around I was not able to get info about these two questions: 1. Is there a function to have a "jackknifed corrected var/cov estimate" (as described in MacKinnon and White 1985) in a standard OLS regression? 2. Does R possess a LAD (Least Absolute Deviation) regression function? Any help? Thanks -- ======================================================== Angelo

Hi, I'm doing robust regression with the following command rlm(dip~ind1+ind2-1,method="M",psi=psi,maxit=1000,acc=1e-15) now when I ask for a summary summary(rlm(dip~ind1+ind2-1,method="M",psi=psi,maxit=1000,acc=1e-15)) I get Coefficients: Value Std. Error t value ind1 -0.0377 0.0000 -24203.1415 ind2 1.0370 0.0000 668735.7195 taht is

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:

If I use the Ineq library and the Gini function in this way: >Gini(c(100,0,0,0)) I obtain the result 0.75 instead of 1 (that is the perfect inequality). I think Gini's formula in Ineq is based on a formula as reported here: http://mathworld.wolfram.com/GiniCoefficient.html but in the case of perfect inequality: x_1=.......=x_n-1 =0 x_n>0 these formula are equal to 1 - 1/n, not to

Hi, I'm trying to write a simple function like case1 <- function (m, cov, Q, R) { theta <- (acos(R/sqrt(Q^3))) beta <- (-2)*sqrt(Q)*cos(theta/3)+m[1]/3 rho1 <- (-2)*sqrt(Q)*cos((theta+2*pi)/3)+m[1]/3 rho2 <- (-2)*sqrt(Q)*cos((theta-2*pi)/3)+m[1]/3 stderrb <- deltamethod( ~(-2)*sqrt(Q)*cos(theta/3)+x1/3,m,cov) stderrr1 <- deltamethod(

Hi there, I am trying to compute Gini coefficients for vectors containing income classes. The data I possess look loke this: yit <- c(135, 164, 234, 369) piit <- c(367, 884, 341, 74 ) where yit is the vector of income classes, and fit is the vector of associated frequencies.(This data is from Rustichini, Ichino and Checci (Journal of Public Economics, 1999) ). In ineq pacakge, Gini( )

Dear All, I wish to calculate the Gini index (ineq from same package) and some other indices for the diameter distribution of each plot (df dgtot). dgtot: IDPlot Diameter(cm) 1 4 34.0 2 4 23.0 3 4 38.0 ... 51 5 16.0 52 5 8.0 53 5 9.0 ... 5301 140 25.0 5302 140 12.0 5303 140 7.0 I use: >

Hello, I would like to build a Lorenz curve and calculate a Gini coefficient in order to find how much parasites does the top 20% most infected hosts support. Here is my data set: Number of parasites per host: parasites = c(0,1,2,3,4,5,6,7,8,9,10) Number of hosts associated with each number of parasites given above: hosts = c(18,20,28,19,16,10,3,1,0,0,0) To represent the Lorenz curve: I

I came across the package 'ineq' that computes a variety of inequality measures (e.g. gini, theil etc). I want to compute the Theil index (racial segregation) and decompose the total into sub-components (by geog levels). I think the package doesn't report the decomposition (correct me if I'm wrong). Just wonder is that available elsewhere? K.

Hello I have a problem when fitting a mixed generalised linear model with the lmer-function in the Matrix package, version 0.98-7. I have a respons variable (sfox) that is 1 or 0, whether a roe deer fawn is killed or not by red fox. This is expected to be related to e.g. the density of red fox (roefoxratio) or other variables. In addition, we account for family effects by adding the mother

R helpers, I am working with the R program performing multivariate regression trees (MRT). I have a matrix with species and environmental variables saved as a CSV file (sprot_matrix.csv), I have 42 species and 8 environmental variables (SECCHI+PH+TA+PTOT+NTOT+CHLA+AREA+ MEANDEP) for 104 samples Title SpA SpB SpC SpD Varible1 Variable2 Variable3 Sample1 Sample 2

Dear All, I have developed a programme the anable the decomposition of the Gini index, it complets tha valuable work of Achim Zeileis, the author of the ineq package. I would like to make it to be part of all R package. How should I proceed. Must I sent it to the the Core developement team ? The proogramme is written in R. Many thanks for your advice, Best regards, Souleymane

Hello. I have a problem using sort() in windows 2000 and windows NT 4.0, running R 1.8.0 on both. I want to sort a vector of characters names, where I have used "Scandinavian" letters, like '?', '?', and '?' (for those who cannot display these letters this question seems rather meaningless, i guess). Windows 2000 sorts the vector like I am used to from other

Hi. I have some data from a survey w/c include income data. Was not quite sure how to generate the gini index on these data. Jose Ramon Albert Statistical Research and Training Center www.srtc.gov.ph -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info",

AFAIK most model fitting techniques will only deal with additive errors, not multiplicative ones. You might want to try fitting: log(y-x) = a*x + e which is linear. Andy > From: Angelo Secchi > > Hi, > is there a way in R to fit a non linear model like > > y=x+exp(a*x)*eps > > where a is the parameter and eps is the error term? > Thanks > Angelo > >

Dear R users, I'm using the "ineq" package to calculate the values ​​of Gini and Lorenz coefficients and to and plot Lorenz graph. I want to plot on the same diagram, curves from two different populations, that have different "n". How can I do this?   Best regards,   Patricia [[alternative HTML version deleted]]

I posted this on R help, and a few others responded indicating they too were able to replicate the error as a function of missing data. I believe this should not be the case and hence and reporting it here. ### Code provided on R-Help by Ivar Herfindal # Simulate data testdata <- cbind.data.frame(gr=3Drep(letters[1:4], each=3D5), = aa=3Drnorm(20), bb=3Drnorm(20)) # Introduce some missingness

I have written the following function to calculate the weighted mean difference for univariate data (see http://www.xycoon.com/gini_mean_difference.htm for a related formula). Unsurprisingly, the function is slow (compared to sd or mad) for long vectors. I wonder if there's a way to make the function faster, short of creating an external C function. Thanks very much for your advice. gmd

Hi all, I apologies in advance if I am missing something very simple here, but since I failed at resolving this myself, I'm sending this question to the list. I would appreciate any help in understanding how the rpart function is (exactly) computing the "improve" (which is given in fit$split), and how it differs when using the split='information' vs split='gini'

Hi, How can I define a new psi function in the rlm comand? In particular I would like to implement the case for \rho(u)=0.5*(u^2) and \psi(u)=u in order to assume normally distributed errors. Any help? Thanks -- ======================================================== Angelo Secchi PGP Key ID:EA280337