similar to: Engel curve

Hi, is there a function in R to convert data read with read.shape and which is originally in UTM coordinates into longitude / latitude coordinates? I found the convUL() function from the PBSmapping package but I have no idea how I could apply that to the read.shape object. Many thanks, Werner __________________________________________________ Do sragenden Schutz gegen Massenmails.

Hi, this is probably the easiest thing to do but I manage not finding the answer: I have a list with matrices of exact same format and headers. Now I would like to transform the list into an normal array. What is the proper way to do this? as.array changes the entire format and right now I only found the method of creating a new array, going through the entire list and copy the matrix in each

Hello Everyone, I'm currently learning about quantile regressions. I've been using an optimizer to compare with the rq() command for quantile regression. When I run the code, the results show that my coefficients are consistent with rq(), but the intercept term can vary by a lot. I don't think my optimizer code is wrong and suspects it has something to do with the starting

Hi! I have large matrices, one column per variable and I have a vector of factors / grouping symbols. Then I am computing subtotals for the groups but it takes pretty long and thus I wanted to ask if there is a better way to do it or if this is already the best way: subTotals <- function(x, groupvec) do.call("rbind",lapply(split(x,groupvec),colSums,na.rm=T)) Thanks reading my

Hi, Before I reinvent the wheel I wanted to kindly ask you for your opinion if there is a simple way to do it. I want to merge a larger number of tables from different data sources in R and the matching criterium are country names. The tables are of different size and sometimes the country names do differ slightly. Has anyone done this or any recommendation on what commands I

Hi, I was wondering if anybody might have a reference for me: My R code is growing and getting more and more confusing. Thus, I figure it's time to switch to object-oriented again. I have done oo programming in C++ and Java before but the first few tutorial on R oo were a bit confusing for me. Is there any brief tutorial on oo programming in R especially for people who have done oo in Java

Dear all, I am having v.4.36 of Quantreg package and I noticed strange behaviour when weights were added. Could anyone please explain me what if the results are really strange or the behavioiur is normal. As an example I am using dataset Engel from the package and my own weights. x<-engel[1:50,1] y<-engel[1:50,2] w<-c(0.00123, 0.00050, 0.00126, 0.00183, 0.00036, 0.00100, 0.00122,

Hi, I have two loosely related questions which could make my live again a bit easier: 1) Is there a simple way to select a range of columns in a data frame using column names? I am thinking of something like mydf[1,"col4":"col8"] 2) I have a data frame with many columns and they all have short variable names which is good in most cases but sometimes it would be nice to have

Hi, I have been dreaming about a complete R environment on my USB stick for a long time. Now I finally want to realize it but what I am missing is a good, portable editor for R which has tabs and syntax highlighting, can execute code, has bookmarks and a little project file management facility pretty much like Tinn-R has those. I like Tinn-R but it seems like there is only a very old version of

Hi there! I am considering to port a SAS application to R and I would like to hear your opinion if you think this is possible and worthwhile. SAS is mainly used to do data management and then to do some aggregations and simple computations on the data and to output a modified data set. The main problem I see is the size of the data file. As I have no access to SAS yet I cannot give real details

Hello, I am very happy that I have Sweave and R to write my papers. But I still have to do some tables by hand since I have not found out how I can customize the latex tables produced by R further (I mainly use xtable()). Like for instance, I have a table which needs an extra row every few rows as a group header and sometimes I want some extra horizontal lines in the table and also a multicolumn

Hi, this is probably a very trivial question but I can't figure out the right terms to find the solution in the list archive. I have a matrix or a data.frame or the like: > m <- matrix(ncol=3,seq(1,9)) > m [,1] [,2] [,3] [1,] 1 4 7 [2,] 2 5 8 [3,] 3 6 9 and now I wonder if one can provide somehow two vectors, one containing row numbers, the other

I?d like to solicit some advice on a debugging problem I have in the quantreg package. Kurt and Brian have reported to me that on Debian machines with gfortran 9 library(quantreg) f = summary(rq(foodexp ~ income, data = engel, tau = 1:4/5)) plot(f) fails because summary() produces bogus estimates of the coefficient bounds. This example has been around in my R package from the earliest days of R,

Hi, since I have quite large tables and the processing takes quite a while I am curious if I can improve the performance of this aggregation somehow: At the moment I am using summaryBy from the doBy package under R 2.4.0, Win2K. summaryBy(soc_s6aq5 + soc_s6aq7 + soc_s6aq9 + soc_s6aq11 ~ hh + comgroup,soc6a,postfix=c("","","",""),FUN=sum, na.rm=T) The

Hi, I have loaded the packages car, memisc, Hmisc and all of these implement the function recode. The order in which the packages are loaded depends on the order I execute my scripts and thus is not always the same and the syntax of the recode function changes with the package. Is there any way to call specificly the memisc recode function? Or maybe it's better to detach all packages first

I've been trying to draw quantile linear regression lines across a scatterplot of my data using attach(forrq) plot(PREGNANT,DAY8,xlab="pregnant EPDS",ylab="postnatal EPDS",cex=.5) taus <- c(.05,.1,.25,.75,.9,.95) xx <- seq(min(PREGNANT),max(PREGNANT),100) for(tau in taus){ f <- coef(rq(DAY8~PREGNANT,tau=tau)) yy <-

Hello, I am just studying the following example from vignette: strucchange-intro, contineousely ending up in an error. This is the given code: 1. library(strucchange) 2. data(USIncExp) 3. if (!"package:stats" %in% search()) library(ts) 4. USIncExp2 <- window(USIncExp, start = c(1985, 12)) A.Modelling: coint.res <- residuals(lm(expenditure ~ income, data = USIncExp2))

Dear all, I want to use the "rearrange" command which is based on Chernozhukov et al paper and is included in the quantreg package. So, I run a quantile regression in which I included dummy variables for state and years in order to estimate the respective fixed effects quantile regression. The problems are the followings: 1. At example that is stated in the help****, I don't

Dear all How can I obtain the data from the function "rearrange" in package quantreg More especifically, based on the example below (available in the help of the rearrange function), how can I access the data generated by "rearrange(zp)" ? data(engel) z <- rq(foodexp ~ income, tau = -1,data =engel) zp <-

Dear All, I am economist and working on poverty / income inequality. I need descriptive statitics like the ratio of education expentitures between different income quintiles where each household has a different weight. After a bit of google search I found 'Hmisc' and 'quantreg' libraries for weighted quantiles. The problem is that these packages give me only weighted quintiles;