similar to: problem for wtd.quantile()

The function wtd.var(x,w) in Hmisc calculates the weighted variance of x where w are the weights. It appears to me that wtd.var(x,w) = var(x) if all of the weights are equal, but this does not appear to be the case. Can someone point out to me where I am going wrong here? Thanks. Tom La Bone [[alternative HTML version deleted]]

Hi, I am doing double for loops to calculate SDs with some weights and wondering if I can get rid of the outer for loop as well. I made a simple examples which is essentially what I am doing. Thanks for your help! -Young #------------------------------------------------------ # wtd.var is Hmisc package # you can replace the 3 lines inside for loop as # sdx[i,] =

Hi everyone, now I am trying to finish writing the code (I had asked for assistance on subtracting arrays) This is what I what I am running in R: > source("/home/ie/Documents/TTU/GA_Research/GLUE/R-Project/R_GLUE_Example/NSEr.R") NSEr <- function (obs, sim) { {jjh <- (as.vector(obs) - sim)^2 Xjjhs <- apply(Xjjh, 2, sum) Yii <- (obs - mean(obs))^2 Yiis <- apply(Yii, 2,

Hello, I was unable to find clues to my problem in ?optim. Using the data and code below, I get an error ("system is exactly singular") when a particular line of code is left in, but have found that 'optim' works when I comment it out. The line of code in question is after the closeAllConnections() line of code and contains a call to "na.approx" from the zoo package.

Hello list, I have the following function which, as you can see, uses mean: meanratings <- round(apply(stack03[,c(102:121)],2,function(x) (tapply(x ,actcode, mean, na.rm=T))), digits=1) The above function yields the following output: q27a q27b q27c q27d q27e q27f q27g q27h q27i q27j q27k q27l q27m q27o q27p 1 7.8 8.1 7.7 7.9 7.9 NaN NaN 8.4 7.8 7.0 7.6 NaN NaN 7.1 6.0 2

Hello, Using this data: http://n4.nabble.com/file/n1676330/US_Final_Values.txt US_Final_Values.txt and the following code i got the image at the end of this message: US.final.values<-read.table("c:/tmp/US_Final_Values.txt",header=T,sep=" ") US.nls.1<-nls(US.final.values$ECe~a*US.final.values$WTD^b+c,data=US.final.values,start=list(a=2.75,b=-0.95,c=0.731),trace=TRUE)

Hello, I probably have a syntax error in trying to generate an expected survival curve from a weighted cox model, but I can't see it. I used the help sample code to generate a weighted model, with the addition of a "weights=albumin" argument (I only chose albumin because it had no missing values, not because of any real relevance). Below are my code with the resulting error

Hello, all. I'm new to R and just beginning to learn to write functions. I know I'm out of my depth posting here, and I'm sure my issue is mundane. But here goes. I'm analyzing the American National Election Study (nes), looking at mean values of a numeric dep_var (environ.therm) across values of a factor (partyid3). I use ddply from plyr and wtd.mean from Hmisc. The nes requires a

Hello everyone, I have tried several ways of doing this and searched the documentation and help lists and I have been unable to find an answer or even whether it is possible to do it. I am pasting together a formula and I need to insert double quotes around the strings. Here's an example: location <- c("AL", "AK", "MA", "PA") v=2 test <-

Hi, I have a data frame with two columns: dt and tf. The dt column is datetime and the tf column is a temperature. dt tf 1 2009-06-20 00:53:00 73 2 2009-06-20 01:08:00 73 3 2009-06-20 01:44:00 72 4 2009-06-20 01:53:00 71 5 2009-06-20 02:07:00 72 ... I need a subset of the rows where the minutes are 53. The hour is immaterial. I can not find a wildcard

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;

I have a binary file(a) with size of (360 720 )for the globe.I wrote the code given below to read and extract an area (south america)from that file. when I use summary for the whole file I got: summary(a, na.rm=FALSE) Min. 1st Qu. Median Mean 3rd Qu. Max. NA's 0.00 1.00 3.00 4.15 7.00 20.00 200083 . But when I used summary for the region(b) which I extracted, I got

I'm looking for a way to improve code that's proven to be inefficient. Suppose that a data source generates the following table every minute: Index Count ------------ 0 234 1 120 7 11 30 1 I save the tables in the following CSV format: time,index,count 0,0:1:7:30,234:120:11:1 1,0:2:3:19,199:110:87:9 That is, each line represents a table, and I

I needed to compute a complicated cross tabulation to show weighted means and standard deviations and the only method I could get that worked uses a series of nested for next loops. I know that there must be a better way to do so, but could use some assistance pointing the way. Here is my working, but inefficient script: library(Hmisc) rm(list=ls()) load('NHTS.Rdata') day.wt <-

I' m trying to compute weighted mean on different groups but it only returns NA. If I use the following data.frame truc: x y w 1 1 1 1 2 2 1 3 1 1 4 2 0 2 1 0 3 2 0 4 1 0 5 1 where x is a factor, and then use the command : tapply(truc$y,list(truc$x),wtd.mean, weights=truc$w) I just get NA. What's the problem ? What can I do ?

Hi Duncan I tried Ecdf and/or wtd.quantile from Hmisc and it is working (probably). Ecdf(x, q=.5) Ecdf(x, weights=xw,col=2, add=T, q=.5) wtd.quantile(x) 0% 25% 50% 75% 100% 10 10 10 100 300 wtd.quantile(x, weights=xw, type="i/n") 0% 25% 50% 75% 100% 10.0000 138.8667 192.5778 246.2889 300.0000 But could you please be more specific in this? >

Hi Petr, I think that Duncan suggests something like this: x<- c(rep(10,20), rep(300,5), rep(100, 10)) tx <- table(x) prop.x <- tx / sum(tx) vx <- as.integer(names(tx)) prop.wx <- tx * vx / sum(tx * vx) plot(ecdf(x)) plot(vx, cumsum(prop.x), ylim = 0:1) plot(vx, cumsum(prop.wx), ylim = 0:1) Best regards, Thierry ir. Thierry Onkelinx Statisticus / Statistician Vlaamse

I have a data frame 'tmp' and a vector 'name' containing 'd2'. I want to save 'tmp' under the name hidden in 'name', and the file must have the same name, plus the extension '.rda'. So I try > tmp x y 1 1 3 2 2 4 > name [1] "d2" > assign(name, tmp) > summary(get(name)) x y Min. :1.00 Min. :3.00 1st

Hello, I'm plotting two sets of data referenced to either the left or right y-axes. The first, water table depth (blue circles), is plotted on the left y-axis in reverse order (0 at the top) as this is more intuitive when thinking in terms of depth. The second is electrical conductance (a surrogate for salinity), and is referenced to the right y-axis. The data and plot commands follow

I am relatively new to R, so apologize up front for my long question, particularly if there is too much or too little information. I have a large time series data set where each subject's behavior was originally coded on .25s intervals for 3min task. I am trying to determine if the findings are different depending on the coding interval (i.e. Compare .25s to 1s to 5s to 10s). I also need to