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- 1 Proposals for restructuring the article
- 2 Free software
- 3 Suggestion - Contrast Time Series with it's alternative(if there is one) for clarity.
- 4 External Link DonQuixote
- 5 References to the (usual) literature
- 6 Properties section or just description section
- 7 Evenly and unevenly spaced time series, wrong examples
Proposals for restructuring the article
I am wondering how to make the article more accessible to the non-expert.
I am also thinking that we need a succinct introduction to time-series with some good motivating examples before we plunge into the detail. I will think a little about how to do this. --Михал Орела (talk) 16:30, 19 October 2008 (UTC)
Image of time series
"Image is everything"!
Well, of course, it is not. But in our modern world it helps if we can attract and inform at the same time. I have chosen a nice image from Wikimedia Commons to illustrate the article. I think it looks good. I think it gives some idea of what a time series might look like and what one might want to do with it. The author has contributed a detailled commentary:
“The data is 1000 points, with a trend of 1-in-100, with random normal noise of SD 10 superimposed. The red-line is the same data but averaged every 10 points. The blue line is every 100 points.
The r2 fit for the raw data is 0.08; for the 10-pt-filtered, 0.57; for 100-pt-filtered, 0.97.
For all series, the least squares fit line is virtually the same, with a slope of 0.01, as expected.
Ignoring autocorrelation, a confidence limit for the fit line is [0.0082, 0.0127] for the raw data (which include 0.01, as it should). For the 10-pt-filtered the limits are slightly narrower at [0.0084, 0.0125] and for the 100pt-filtering the limits are again slightly narrower.
So what does that all mean?
for the raw data, the simple trend line explains almost none of the variance of the time series (only 8%). for the 100-pt filtering, the trend line explains almost all of the data (97%). nonetheless, the trend lines are almost identical as are the confidence levels.
The time series are, of course, very closely related: the same except for the filtering. This shows that a low r2 value should not be interpreted as evidence of lack of trend.”
what is time series data and give examples
// Changed the one section to Applied Time Series, which is IMO better than "Industry" // Added Multiscale to the introduction to reflect recent developments // THIS IS NOT part of economics, Time Series is STATISTICS. Econometrics is the topic that should be "part" of economics, the two are linked but SEPERATE. —Preceding unsigned comment added by 184.108.40.206 (talk) 11:17, 16 September 2007 (UTC)
Nearly all the links to software are for pay-for stuff - could not some links to free software be included also? I am not an expert on relevant software myself.
What does the alpha term mean in the time series, and what is the significance of Y? Is it the sum of all of the terms? Why would you want to do that? —Preceding unsigned comment added by 220.127.116.11 (talk) 19:13, 8 January 2008 (UTC)
Suggestion - Contrast Time Series with it's alternative(if there is one) for clarity.
Is there an alternative representation of data other than Time series? Frequency Series maybe? If someone could mention an alternative and contrast it in the introduction it would greatly clarify what Time-series are, besides being a fancy name for a bunch of data points with time as one of the dimensions.Krymson (talk) 23:38, 2 February 2008 (UTC)
- Have added something on problems that are not "time series". Melcombe (talk) 14:46, 15 February 2008 (UTC)
External Link DonQuixote
I have added a link to the home page of DonQuixote time series software. It is one of the few free time series software available. It is probably the only free software which includes free GPL source code in C++. It is a quite extensive package with more tha 100000 lines of C++ source code. The linked web site does not include anything else than the homepage of the free time series software. —Preceding unsigned comment added by Truswalu (talk • contribs) 14:32, 29 March 2008 (UTC)
- Please read the external link guidelines I've provided you; specifically, links requiring registration to view the 'content'. Thanks. Kuru talk 15:10, 29 March 2008 (UTC)
References to the (usual) literature
It is usually a good idea to cite the published literature (in addition to web pages). The Time series field is well-established. I will add in the appropriate section now and list one text to get started.--Михал Орела (talk) 14:11, 19 October 2008 (UTC)
Properties section or just description section
I want to list all possible properties of a time series: volatile, persistent, stationary vs. explosive, mean reverting vs. structure break, and so on. Also a list of possible properties of several time series: related or not, cointegrated or not, and so on. Jackzhp (talk) 20:36, 18 May 2011 (UTC)
Evenly and unevenly spaced time series, wrong examples
The article again says "a time series is a sequence of data points, measured typically at successive times spaced at uniform time intervals. Examples of time series are the daily closing value of the Dow Jones index ". Well the Dow Jones Index is exactly an example of a time series that is NOT evenly spaced: It is published only on trading days, so the interval between values is often 24 hours but also very often 23 or 25 hours (daylight saving changes) or several days (weekends, holidays). Generally, time series analysis processing has often to do with real world events like transactions at a stock exchange. A live feed of transactions about a certain stock will deliver values in random timely order: There are seconds were several transactions occur and there are hours were nothing happens. I would also remove the restriction that a time series is a measurement, because transactions at an electronic exchange for instance are computed by the computer there and communicated afterwards. I suggest a time series definition that says that defines it as an sequence of values each having a time and ordered by time. — Preceding unsigned comment added by Thulka (talk • contribs) 12:22, 12 January 2012 (UTC) The second example, yearly flow is not evenly spaced either, as gregorian calendar years to not have constant length due to leap year and second effects. The example I brought in here with the audio sampling was a correct example.
The article on unevenly space time series is good, but the insight that nearly all natural observations are unevenly spaced is missing from this article.