similar to: Time series: xts/zoo object at annual (yearly) frequency

R-listers, I am using xts with a yearmon index, but am getting some inconsistent results with the date index when i drop observations (for example by using na.omit). The issue is illustrated in the example below. If I start with a monthly zooreg series starting in 2009, yearmon converts this to "Dec-2008". Not such a worry for my example, but strange. Having converted to xts, i drop

Hi, I cannot figure out how to change the index format when displaying POSIXct objects. Would like the xts index to display as %H:%M:%OS3 when doing viewing the xts object. Think I am missing the obvious. Cheers, Chris -- View this message in context: http://r.789695.n4.nabble.com/xts-POSIXct-index-format-tp3336136p3336136.html Sent from the R help mailing list archive at Nabble.com.

hello, Does anybody know how to aggregate a lag series ? when I try to use aggregate I get the following message > try<-ts(1:100,start=c(1985,1),freq=12) > aggregate(try,4,mean,na.rm=T) Qtr1 Qtr2 Qtr3 Qtr4 1985 2 5 8 11 1986 14 17 20 23 1987 26 29 32 35 1988 38 41 44 47 1989 50 53 56 59 1990 62 65 68 71 1991 74 77 80 83 1992

hey I am trying to turn a dataframe into xts with the function: as.xts, but it returns the error: Error in as.POSIXlt.character(x, tz, ...) : character string is not in a standard unambiguous format could someone give me some pointers please the data is coming from a spreadsheet via the excel, and has 5 columns of data (date (with the date and time), open, high, low, close) (excel format) ela

I would like to add vertical shaded blocks in plot.xts graphs (like recession periods in FRED graphs) The reason I use plot.xts instead of plot.zoo is that I like the fact that the grid is automatically aligned with major ticks in plot.xts. xblocks() and rect() do not seem to work with plot.xts (only with plot.zoo). Are there any alternative methods that work with plot.xts? Thanks. -- View

Is there an elegant way to do operations (+/-/*/ / ) on zoo/xts objects when one serie is monthly (end of month) and the other daily (weekdays only) - typically a monthly economic indicator and a stock index price? Thanks, TDB -- View this message in context: http://r.789695.n4.nabble.com/How-to-do-operations-on-zoo-xts-objects-with-Monthly-and-Daily-periodicities-tp3558081p3558081.html

Dear R users, I am currently working in subsetting a zooreg() object using either window or subset. I have a solution but it may be a bit cumbersome when I start working with actual data. Your inputs would be greatly appreciated. Example: I have a zooreg() object that starts in 1997 and ends in 2001. This object contains daily data for the 4 years

I have a zooreg object and I want to be able to generate a value for seasons and 11-day composites paste it onto my zoo data frame, along with year, month and days. Right now I have the following to work from: eg. dat.zoo.mdy <- with(month.day.year(time(dat.zoo)), cbind(dat.zoo, year, month, day, quarter = (month - 1) %/% 3 + 1, dow = as.numeric(format(time(dat.zoo), "%w")))) For

Folks, I have some weekly dataseries that I convert to monthly xts (with yearmon indices), and obtain the two following extracts: > str(sig) An 'xts' object from Apr 1998 to Sep 1998 containing: Data: num [1:6, 1] 0.0083 0.2799 -0.2524 -0.0119 0.18 ... - attr(*, "dimnames")=List of 2 ..$ : NULL ..$ : chr "e1" Indexed by objects of class: [yearmon] TZ:

Hullo I may have missed something blindingly obvious here. I'm using xts to handle some timeseries data. I've got daily measurements for 100 years. If I try to reduce the error rate by taking means of each month, I'm getting what at first sight appears to be conflicting information. Here's a small subset to show the problem: A small set of data: > vv x

I have financial data on a a set of firms, with a quarterly period (fundamental data). The data spans 10 years, and four quarters per year. The present file (.csv) reads the Date columns as "200706" for the second quarter of 2007; "199809" for the third quarter of 1997. Is there a way I can convert it to something like "2007 Q2", "1998 Q3"? I am aware of

Hi Guys, I'm using zoo package now. I found lag is not doing what I assumed. > x <- zoo(11:21) > z <- zoo(1:10, yearqtr(seq(1959.25, 1961.5, by = 0.25)), frequency = 4) > x 1 2 3 4 5 6 7 8 9 10 11 11 12 13 14 15 16 17 18 19 20 21 > lag(x) 1 2 3 4 5 6 7 8 9 10 12 13 14 15 16 17 18 19 20 21 > z 1959 Q2 1959 Q3 1959 Q4 1960 Q1 1960 Q2 1960 Q3 1960 Q4

Hello, I'm very new to R, and so my question is simple. I have data record with 80 years of daily temperatures in one long string. The dates are also recorded, in YYMMDD format. I'd like to learn an elegant simple way to pull out the annual averages. (Obviously, every 4th year has 366 days.) I know I can set up a formal loop to create annual records and then average. But R

Hello, I'd like to convert the below time-series data with fft or wavelet related function and plot it. Could you let me know 1. How to convert xts data frame format to list format ? 2. How to plot fft or wavelet diagram ? Here is the data : &gt; class(zc) [1] "xts" "zoo" &gt; str(zc) An ‘xts’ object from (10/15/12 09:00:00) to (10/15/12 15:15:00)

Is there a easy way to create the time index for a zoo/xts object for every 100 milliseconds. eg. time Index would be: 10:00:00:100 10:00:00:200 10:00:00:300 10:00:00:400 I am looking to build an empty zoo/xts object with time index from 10am to 3pm, index jumps by 100ms each row. Thanks, Chris -- View this message in context:

library(xts) library(TTR) ndx = getYahooData("^NDX") aa = ndx$Close bb = aggregate(aa, as.yearweek, tail, 1) The last operation takes forever, and then the bb dates are messed up. The following produces the desired result: time(aa) = as.Date(time(aa)) bb = aggregate(aa, as.yearweek, tail, 1) The index of ndx and aa is of POSIXct (as reported by is(time(ndx))) , which apparently

Hello, I am writing codes for time series computation but encountering some problems Given the quarterly data from 1983Q1 to 1984Q2 PI1<-ts(c(2.747365190,2.791594762, -0.009953715, -0.015059485, -1.190061246, -0.553031799, 0.686874720, 0.953911035), start=c(1983,1), frequency=4) > PI1 Qtr1 Qtr2 Qtr3 Qtr4 1983 2.747365190 2.791594762

Looking for a little help figuring out what's driving gaps in data after merging two xts objects (msci.m and x2). The merge statement I'm using is ... y <-merge(x2,msci.m, all=FALSE). Here's info on the output , y: head(y) t-bill msci Sep 1985 7.310 316.963 Mar 1986 6.560 463.471 Jun 1986 6.180 498.791 Jul 1987 6.200 778.898 Aug 1987 6.400 833.519 Nov 1987

Dear all, please consider my following workbook: library(zoo) lis1 <- vector('list', length = 2) lis2 <- vector('list', length = 2) lis1[[1]] <- zooreg(rnorm(20), start = as.Date("2010-01-01"), frequency = 1) lis1[[2]] <- zooreg(rnorm(20), start = as.yearmon("2010-01-01"), frequency = 12) lis2[[1]] <- matrix(1:40, 20) lis2[[2]] <-

Hello, I'm very interested in using financial time series data, but I'm a beginner of R programming. I'd like to fully understand internal logics on several time-series related packages such as quantmod, xts, zoo, chron, etc. So, I read some books, 'R Cookbook' and 'Art of R Programming' and another simple tutorials. But I still can't understand grammars of the