similar to: Filtering out a data.frame

Hello Everyone, I just started a new job & it requires heavy use of R to analyze datasets. I have a data.table that looks like this. It is sorted by ID & Date, there are about 150 different IDs & the dataset spans 3 million rows. The main columns of concern are ID, date, and totret. What I need to do is to derive daily returns for each ID from totret, which is simply totret at time

Dear R Gurus, Thanks for any help in advance! Date.frame: Returns.names X id ticker date_ adjClose totret RankStk 258060 258060 13645T10 CP 2001-06-29 18.125 1877.758 My data frame is in the above format. I would like to filter by period, per id (every 125 days) each consisting of 250 days, I.e. 1-250, 126-375, etc. One important thing to note is that not all

hey guys, I am working on a function to make a duplicated value unique. For example, the original vector would be like : a = c(2,1,1,3,3,3,4) I'll like to transform it into: a.nodup = 2, 1.01, 1.02, 3.01, 3.02, 3.03, 4 basically, find the duplicates and assign a unique value by adding a small amount and keep it in order. I come up with the following codes, but it runs slow if t is large. Is

Hey Everyone, I have been stumped by this all day. Basically, I have a data.frame of multiple columns. Of concern are "id" & "date" For some reason, oftentimes there are duplicates of data with the same date. I would like to remove the duplicates per different id (removing duplicate dates for the entire data.frame would leave nothing since different id's all have

I have two datasets, big and small. s_date<-c(?2005-12-02?, ?2005-12-01?, ?2004-11-02?,?2002-10-05?,?2000-12-15?) s_id<-c(?a?,?a?,?b?,?c?,?d?) b_date<- c(?2005-12-31?, ?2005-12-31?, ?2004-12-31?,?2002-10-05?,?2001-10-31?,?1999-12-31?) b_id<-c(?a?,?b?,?c?,?d?,?e?,?c?) small<-data.frame(date_=as.Date(s_date),id=s_id) big<-data.frame(date_=as.Date(b_date),id=b_id) For each row

I am running R 2.1.1 in a Microsoft Windows XP environment. I have a matrix with three vectors (“columns”) and ~2 million “rows”. The three vectors are date_, id, and price. The data is ordered (sorted) by code and date_. (The matrix contains daily prices for several thousand stocks, and has ~2 million “rows”. If a stock did not trade on a particular date, its price is set to “NA”)

Dear useRs, I am stuck with a piece of code and hope you could give me some pointers. My aim is to calculate the lm-regression coefficients of individual stocks against an index. I am interested in both the coefficient and the pval. While I could do this manually for a select hand full, I hope to scale this up say for 30+ stocks (DAX-30, FTSE-100 etc.) to eventually have a matrix of coefficients

Within an R dataset, I have a date field called “date_”. (The dates are in the format “YYYY-MM-DD”, e.g. “1995-12-01”.) How can I add or subtract “1 month” from this date, to get “1996-01-01” or “ “1995-11-01”. --------------------------------- [[alternative HTML version deleted]]

Data processing? I have a large number of csv files from animal tracks that look like this: Date_ Time_ Speed Course Type_ Distance 30/03/2012 11:15:05 108 121 -2

Hello, I have a few questions concerning the DCC-GARCH model and its programming in R. So here is what I want to do: I take quotes of two indices - S&P500 and DJ. And the aim is to estimate coefficients of the DCC-GARCH model for them. This is how I do it: library(tseries) p1 = get.hist.quote(instrument = "^gspc",start = "2005-01-07",end =

Hi, the snippet of code below works, but I would like to know how to feed the function merge.zoo the contents of CADstocknames rather than having to hard code it into the merge.zoo command. I think I must be missing something simple, but I cannot for the life of me figure it out. Thanks in advance for any enlightenment offered. library(zoo) CADstocknames <-

All, I have been just recently working with zoo objects for trading systems. Can someone please help with these basic questions? Given a daily time series downloaded using get.hist.quote() from the tseries package, ie...... startDate= as.Date("2000-01-01") endDate= as.Date("2011-01-29") frequency= 'd' s= get.hist.quote('IWF', start= startDate, end=

Dear R Gurus, As you probably know, dist calculates the distance between every two rows of data. What I am interested in is the actual two rows that have the least distance between them, rather than the numerical value of the distance itself. For example, If the minimum distance in the following sample run is d[14], which is .3826119, and the rows are 4 & 6. I need to find a generic way to

Hello, I have a rather complex problem... I will have to explain everything in detail because I cannot solve it by myself...i just ran out of ideas. So here is what I want to do: I take quotes of two indices - S&P500 and DJ. And my first aim is to estimate coefficients of the DCC-GARCH model for them. This is how I do it: library(tseries) p1 = get.hist.quote(instrument =

I''m doing some incremental improvements on scaffolding, and want to add in-place editing to an admin section. I think I may have the view part working right (at least, the editor pops up as expected) with this in my view: ### <% for link in @links %> <tr> <td> <div id="<%= ''url'' + link.id.to_s -%>"><%= link.url

I found an example at http://www.bearcave.com/finance/random_r_hacks/kalman_smooth.html shown below. But it seems the structSSM function has been removed from KFAS library so it won't run. Does anyone know how to fix the code so that it runs? library(KFAS) library(tseries) library(timeSeries) library(zoo) library(quantmod) getDailyPrices = function( tickerSym, startDate, endDate ) {

Hi R users,   Thanks in advance.   I am using R 2.12.0 on Windows XP.   May I request you to assist me in the following please.   1. I am getting error while downloading quote data from yahoo finance.   The example code is below (taken from tseries help):   library(tseries)   con <- url("http://quote.yahoo.com") if(!inherits(try(open(con), silent = TRUE), "try-error")) {  

Hello, I have a rather complex problem... I will have to explain everything in detail because I cannot solve it by myself...i just ran out of ideas. So here is what I want to do: I take quotes of two indices - S&P500 and DJ. And my first aim is to estimate coefficients of the DCC-GARCH model for them. This is how I do it: library(tseries) p1 = get.hist.quote(instrument =

> structSSM Is no longer part of KFAS. All you needed to do was: library(KFAS) ?KFAS and you would have seen that if you went to the index. A structural state space model is now built up from its components, much like in LM. Look at; ?SSModel -Roy > On Jul 29, 2017, at 9:26 PM, Staff <rbertematti at gmail.com> wrote: > > I found an example at >

Hello This is my first post on this forum and I hope someone can help me out. I have a datafile (weeklyR) with returns of +- 100 companies. I acquired this computing the following code: library("tseries"); tickers = c("GSPC" , "BP" , "TOT" , "ENI.MI" , "VOW.BE" , "CS.PA" , "DAI.DE" , "ALV.DE" ,