similar to: ts.intersect a multivariate and univariate ts

Hello! Recently I got report that my package mar1s doesn't pass checks any more on R 3.0.2. I started to investigate and found the following difference in multivariate time series handling in R 3.0.2 compared to R 2 (I've checked on 2.14.0). Suppose I wish to calculate seasonal component for time series. In case of multivariate time series, I wish to process each column independently.

{all recent versions of R} Problem / design bug : diff.default() doesn't deal with "ts" objects properly, diff.ts() does, but that is only available from package "ts" where as the constructor function ts() is in base. It's not sufficient to just move diff.ts() to package base, since it relies itself on lag & lag.default which are also only in package ts.

I have a suggestion for kernapply for ts objects. When we choose the option circular=F, the returned series don't have the correct dates. The removed dates are all at the beginning instead of half at the beginning and half at the end. It is particularly useful when we need to smooth the series (or remove a trend using a filter) before estimating a model (like in macroeconomics) or simply

I'm trying to convert a column of a table into a ts object. The data is monthly, so I want the ts frequency to be 12. I did this ... > filings.ts = as.ts(Filings.100K, frequency=12) > filings.ts Time Series: Start = 1 End = 311 Frequency = 1 [1] 246.9336 305.6789 ... ... > tsp(filings.ts) [1] 1 311 1 > tsp(filings.ts) <- c(1,311,12) Error in attr(x, "tsp")

Dear Helpers, I am looking for methods and tools to compare and then to concatenate two successive time series. They are both in the same frequency and they describe one phenomena. There is no time gap between them. The problem is that the method of measurements has changed between both time series and they are no statistically the same. I would like to merge them to receive one homogeneous

There is now a preliminary version of a time series package in the R-devel snapshots, and we would welcome feedback on it. It is based in part on the packages bats (Martyn Plummer) and tseries (Adrian Trapletti) and in part on code I had or have written. (Thanks for the contributions, Martyn and Adrian!) Some of the existing ts code has been changed, for example to plot multiple time series, so

Thanks for the very detailed explanation. I did not create the series using structure(), that was the result of dump() on an intermediate object created within tsdisagg::ta(), which is where I found the error in the first place. ta() indeed manipulates .Tsp directly, rather than using ts. I guess this is a bug in tsdisagg then. Thanks! -- Andrea Altomani On Sat, Sep 2, 2017 at 12:31 AM

I'm probably apporaching this all wrong to start but.... Suppose I have a monthly time series and I want to compute the mean of months 6,7, and 8. I want to plot the original time series and the seasonal time series, one above the other. When I do that as below the time series don't line up for reasons that are obvious. How can I change the base of the seasonal time series so I can make

Hi all. Currently, if you try: > lag.plot(1:10) you get superposed labels '1' and '10'. Things go worse in more extreme cases: x <- ts(1:10) x1 <- lag(x, 4) plot(x1, x) This is due to a mistake in plot.ts. My suggestion is the following really minimal patch to plot.ts: @@ -530,7 +530,7 @@ plot.ts <- text(xy, labels =

I think this is another one of the same kind of bugs in ts: Version 0.64.1 (May 8, 1999) ... > z <- ts(matrix(1:20,10,2), start=c(1969,1), frequency=12) > (z > 5) | (z < 2) Error: invalid time series parameters specified > Paul -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-devel mailing list -- Read

This message is in MIME format --_=XFMail.1.3.p0.Linux:990702182137:16900=_ Content-Type: text/plain; charset=us-ascii There was some discussion a while back on R-devel between Ross Ihaka, Paul Gilbert and myself about row subsetting in time series. I think the consensus was that "[.ts" should not try to coerce its result back to a time series object (which is underlying the problem

On Fri, 1 Sep 2017, Andrea Altomani wrote: > I should have formulated my question in a more specific way. > > 1. I suspect this is a floating point precision issue. I am not very > knowledgeable about R internals, can someone else confirm it? Yes. If you represent a series with increment 1/12 it depends on how you do it. As a simple example consider the following two descriptions

>>>>> On Fri, 02 Jul 1999, Adrian Trapletti <Adrian.Trapletti@wu-wien.ac.at> said: Adrian> There seems to be a problem with plot.ts (R Version 0.64.2) > x<-cbind(1:10,2:11) > x<-as.ts(x) > plot(x) Adrian> Error: subscript (20) out of bounds, should be at most 10 This is definitely a bug --> CC: R-bugs ALL NOTE : This is *not* new

I should have formulated my question in a more specific way. 1. I suspect this is a floating point precision issue. I am not very knowledgeable about R internals, can someone else confirm it? 2. Should this be considered a bug or not, because it is "just a precision issue"? Should I report it? 3. How can it happen? From a quick review of ts.R, it looks like the values of the time

Hi all- I am trying to use the time function for ts class objects and do not understand the return value. I want to use it to set up a time trend in arima fits. It does not seem to return a correct linear sequence that matches the underlying time series. I am running: R version 2.8.1 (2008-12-22). For example: R> ## create a time series R> x <- rnorm(24) R> (xts <-

Paul wrote to R-devel : PaulG> ts() is giving me problems on Solaris: PaulG> R : Copyright 1999, The R Development Core Team PaulG> Version 0.64.0 (April 8, 1999) PaulG> ... >> z <- ts(matrix(1:20,10,2), start=c(1969,1), frequency=12) >> max(abs(z-z)) PaulG> Error: invalid time series parameters specified >> traceback()

I have a time series x, and two other series obtained from it: x <- structure(2017, .Tsp = c(2017.41666666667, 2017.41666666667, 12), class = "ts") y <- floor(x) z <- x-y I would expect the three series to have exactly the same index. However I get the following > time(x)-time(y) Jun 2017 0 as expected, but > time(x)-time(z) integer(0) Warning message: In

Marcus Eger <marcus.eger@physik.uni-marburg.de> writes: > > time(sqrt(arrts)) > Time Series: > Start = c(1, 1) > End = c(5, 1) > Frequency = 1 > [1] 1 2 3 4 5 Looks like a bug... > ---------------------------------------------------------------------------- > 2. (At least) boolean indexing with matrices does not seem to work > properly: >

Hello, I am wondering how I should set up the tsp attribute (available through attr(x, "tsp")) of a dataset x? Let's assume that x has 100 points, and I want to set the frequency to 4. I tried: > attr(x,"tsp")<-c(1,100,4) Error in attr(x, "tsp") <- c(1, 100, 4) : invalid time series parameters specified Is there any other way to set the frequency of

Greetings, I am having trouble getting the function reformulate_ATSP_as_TSP to work for me. I have provided a simple example of some of the code I've been using. In particular, I'm not sure why I'm getting the error "Error in dimnames(tsp) <- list(lab, lab) : length of 'dimnames' [1] not equal to array extent" since I created the object ATSP with a valid