similar to: xts and data.frame question

Dear R help I was hoping you might be able to show me how to write a loop function take would ccomplish this task. library(prob) { a <- sample ( 1:20, 100, replace=T) b<-sample(5:24,100,replace=T) } dd <- data.frame(a,b) dd # code piece I am looking for if(subset(dd,c(1,23,ordered=F))is found))( print subset) else( continue evaluating subsets) subset(dd,isin(dd,c(1,23), ordered =

Hi David, I tried the following and get the below error messages.... con = blpConnect(show.days="trading",na.action="previous.days",periodicity="da ily")# connecting Bloomberg > dat <- blpGetData(con,"US4009703799 Equity","PX_LAST",start=as.chron(as.Date("01/01/2005",

I am trying to use if...else loop and have included a code snippet which I might like to expand. Maybe you could steer me in the right direction. library(stats) library(prob) { a <- sample ( 1:4,100, replace=T,prob=c(0.1,0.2,0.5,0.3)) b<-sample(3:6,100,replace=T,prob=c(0.2,0.2,0.2,0.4)) } dd <- data.frame(a,b) if (subset finds a vector) ( print that vector) (else

I'm doing these manipulations on the data frame and wondering why does R have to remember historical data on my operation and not just keep the needed info. Probably a basic fundamentals of the way R handles data .. Pls point me to the manual if possible .. I have this Index data: > head(NIFTY_INDX) Constituents.list.of.S.P.CNX.Nifty X X.1 X.2 X.3

Hello everybody. I found out the other day something quite astonishing (which I guess is not astonishing at all to those in the know): in d-dimensional space, determining whether a given point is inside the convex hull of a set of n points is elegantly and quickly solvable using linear programming. If the columns of matrix "ff" are the coordinates of the set of points, then in d=2

Hi, I am an R novice working with financial data. I am developing a portfolio strategy evaluation technique to back-test the performance of our screens; checking how the screened stock would've performed over the period in question. I am using quantmod in R to download the historical data from yahoo and then analyzing it using PerformanceAnalytics. My problem is that, as our screens are done

Hi R, Can I convert ISIN numbers into Bloomberg tickers in the RBloomberg package? BR, Shubha [[alternative HTML version deleted]]

I''ve seen this happen before, not sure why. I changed ''phy:'' to ''file:'' and it worked. I later rebooted and ''phy:'' worked again. So you might try ''file:'' rather than ''phy:''. -- Ray -----Original Message----- From: xen-users-bounces@lists.xensource.com

Dear Jim, Here is again exactly what I did and with the output of Rprof (with this reduced dataset and with a simpler function, it is here much faster than in real life). Thanks you again for your help! ## CODE ## mydata1<- structure(list(species = structure(1:8, .Label = c("alsen","gogor", "loalb", "mafas", "pacyn", "patro",

Hi, I''m learning puppet as that is what they use at my current work, though that could change... Question 1: Last place of work, we wrote our own perl based system which was extremely simple and concise to drive - eg to distribute a file, we would put it in: <nfsdir>/noarch/dist/etc/syslog-ng/syslog-ng.conf/ # which means create a file /etc/syslog-ng/syslog-ng.conf on the

Hello, I'm a R newcomer and I'm wondering the kind of data structure that would best fit to my problem: my data are equities (stocks) : so I have a time serie (say 1 year of weekly data), and a bunch of qualitative + quantitative variables : the sector of the stock (biotech/finance...), the geographical region, the name, ISIN code, P/E ratios, whatever... The data.frame is perfect for the

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I was wondering why I get <NA> instead of the timestamp in the following. Thanks. > dataDir <- file.path(wd) > localRaw <- read.csv(file.path(dataDir,"LOCAL.csv"), as.is=T,stringsAsFactors = FALSE) > localRaw[1:2,] Year Month Day hour minute second Temp1mab Temp7mab Temp14mab Salinity1mab 1 2009 10 5 0 0 0 11.288 13.675 13.743 33.513

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Hi, I'm trying to use transform my mercator locations into utm but I'm doing something wrong because only x is transformed ... see > xy.sp SpatialPoints: loni lati [1,] -8.85 38.16 [2,] -9.19 37.99 [3,] -9.11 37.97 [4,] -9.06 38.15 [5,] -9.03 37.87 [6,] -9.14 37.81 [7,] -9.09 37.70 [8,] -8.95 37.45 [9,] -9.17 37.37 [10,] -9.00 37.34 Coordinate Reference

Hi! The kernlab function kpca() mentions that new observations can be transformed by using predict. Theres also an example in the documentation, but as you can see i am getting an error there (As i do with my own data). I'm not sure whats wrong at the moment. I haven't any predict functions written by myself in the workspace either. I've tested it with using the matrix version and the

A question about comparing symptom reduction over time and across treatment groups. Each respondent is asked twice if they experience symptoms (coded 1), at baseline and then at 6 months later. They are randomly assigned to either the control or the intervention group. The 2x2x2 table below shows the frequency counts. As can be seen in the margins of the table, 21% of the control group