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Problem 1: Often, when I'm dealing with its, str() breaks. Here's a bug demo. The first statements work fine -- library(its) # Make a series of all dates from 1/1/2000 to 10/1/2000; fill this up # with integers from 1 to 30 x1 <- newIts(start="2000-01-01", end="2000-01-10", 1:30, ncol=3) print(x1) # Do the same, but restrict yourself to weekdays only x2 <- newIts(start="2000-01-01", end="2000-01-10", 1:30, ncol=3, extract=T, weekday=T) print(x2) str(x1) # works But her...

...I'm trying to learn `its' and am stuck on many basics. Could you please help? I am on R 1.9.1 (2004-06-21) on Linux 2.4.17 #2. My its version says Packaged: Tue Apr 27 13:38:25 2004; HeywoodG Built: R 1.9.0; ; 2004-04-28 15:03:13; unix This part flows fine -- library(its) x1 <- newIts(start="2000-01-01", end="2000-01-10", 1:30, ncol=3) print(x1) x2 <- newIts(start="2000-01-01", end="2000-01-10", 1:30, ncol=3, extract=T, weekday=T) print(x2) Now I get into trouble -- str(x1) # works str(x2) # BREAKS For the str(x2)...

Hi ggplot experts, I need to plot two time series of stacked data: a barchart with bars for each month. To compare the data of two years I need to combine both time series with in a single graph via position=doge. How should I do that? I tried the following scenario: I added two layers with the time series of the stacked data for both years. That worked well exept the bars are obscuring each

I find it's just great to be able to say: library(tseries) x <- get.hist.quote(instrument="ongc.ns") and it gets a full time-series of the stock price of the symbol ongc.ns from Yahoo quote. However, once my hopes have been raised by such beauty :-) I get disappointed when I do > plot(x) and the annotation is horrible! The x axis is not labelled as dates. The default

Hi All: I'm new to R and have a few questions about getting R to run efficiently with large datasets. I'm running R on Windows XP with 1Gb ram (so about 600mb-700mb after the usual windows overhead). I have a dataset that has 4 million observations and about 20 variables. I want to run probit regressions on this data, but can't do this with more than about 500,000 observations before