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This topic is inconsistent about hyphenating the term "time series" as a standalone noun (time series/time-series) and as a modifier (time series analysis/time-series analysis). Can someone decide?

I am wondering how to make the article more accessibleto the non-expert.

I am also thinking that we need a succinct introduction to time-serieswith 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)[reply]

"Image is everything"!

Well, of course, it is not. But in our modern world it helps if we can attractand inform at the same time. I have chosen a nice image from Wikimedia Commonsto 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.”

and also provided source code.--Михал Орела (talk)07:26, 20 October 2008 (UTC)[reply]

62.56.97.111 (talk)23:29, 18 November 2007 (UTC) Does need examples towards the beginning of the article[reply]

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.—Precedingunsigned comment added by82.32.9.240 (talk)11:17, 16 September 2007 (UTC)[reply]

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?—Precedingunsigned comment added by192.85.47.12 (talk)19:13, 8 January 2008 (UTC)[reply]

Will do—Precedingunsigned comment added by62.30.156.106 (talk)18:31, 23 January 2008 (UTC)[reply]

I nixed Mathematica, if this is a thing I'll nix a couple more. It's a bit strange to me because I really don't hear about the paying ones at all. Reason being if it's proprietary, then you don't get the community writing code and packages for it, so it becomes much less useful. Ie for what I do in time series people don't talk about Mathematica at all full stop. It's all free open source stuff like Python and R. Python has TF, Keras, and PyTorch, Mathematica has nothing. So I'm right there with you guys on that. It's not that I'm against proprietary software, but for the stuff that I do, the only proprietary software I hear about is CUDA, and that's something related but different.Alcibiades979 (talk)00:58, 30 July 2019 (UTC)[reply]

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)[reply]

Have added something on problems that are not "time series".Melcombe (talk)14:46, 15 February 2008 (UTC)[reply]

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.—Precedingunsigned comment added byTruswalu (talk •contribs)14:32, 29 March 2008 (UTC)[reply]

Please read the external linkguidelines I've provided you; specifically, links requiring registration to view the 'content'. Thanks.Kuru^talk15:10, 29 March 2008 (UTC)[reply]

It is usually a good idea to cite the published literature (in addition to web pages). TheTime 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)[reply]

Now that the section is in place (with one book reference) the next step will be to introduce an appropriate (foot)notes section. I will do this now.--Михал Орела (talk)14:30, 19 October 2008 (UTC)[reply]

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)[reply]

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.— Precedingunsigned comment added byThulka (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.[reply]

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.

What is the exact name of this notiontime series ortime sequence(s)? Is not a sequence? This aspect is useful to be clarified.--5.2.200.163 (talk)14:56, 25 September 2017 (UTC)[reply]

You could argue that the concept should logically be called a "time sequence", becauseseries in mathematics implies that the terms are summed. But "time series" (however illogical it may be) is the common name for this concept, so ourarticle titles policy says that is what the article should be called.Gandalf61 (talk)15:05, 25 September 2017 (UTC)[reply]

I think that some historical aspects about the how the nametime series in current form has becomed what it is and who has named it this way instead oftime sequence should be added to the article. (I also notice that this rather improper name has been passively(?) adopted by translation in languages other English).--5.2.200.163 (talk)09:23, 3 October 2017 (UTC)[reply]

The article currently contains this list:

1. CRAN supplementary statistics package forR^[1]
2. Analysis and Forecasting withWeka^[2]
3. Predictive modeling withGMDH Shell^[3]
4. Functions and Modeling in theWolfram Language^[4]
5. Time Series Objects inMATLAB^[5]
6. SAS/ETS inSAS software^[6]* Expert Modeler inIBM SPSS Statistics and IBMSPSS Modeler
7. Automatic Time series Forecasting withLDT^[7]*EViews is a statistical package for Windows, used mainly for time-series oriented econometric analysis.
8. bayesloop: Probabilistic programming framework that facilitates objective model selection for time-varying parameter models^[8]
9. Slycat Web-based ensemble analysis and visualization platform, created at Sandia National Laboratoriesl^[9]
10. Seglearn: open source python package andscikit-learn extension for machine learning with time series and sequence data^[10]

All the references here are primary (i.e. not independent from the package), and some are not notable (in Wikipedia terms). Though I am familiar with some of the packages here, I doubt for others that they are particularly known outside of the selected field (and the sources certainly don't show it). Those that do not have their own wikipedia article should have sources which are both independent (secondary) and reliable, showing that they should be included in this list (basically, 'notable' use of the functions named in this article). Such sources could also include reliable comparisons/reviews of the packages (where that could be a general source for the section).

I've asked today for independent sourcing to be able to show that packages warrant being included in this list. In about a month any that do not have any independent sourcing showing that they belong in this list, AND do not have their own article to show that they are notable should be cleared from this list. --Dirk Beetstra^TC11:05, 28 September 2018 (UTC)[reply]

The introduction describe time series as a mathematical concepts. Seems like it is more a word used in economics or practical science that mathematician would call a stochastic or a random process.200.110.171.141 (talk)19:28, 7 February 2025 (UTC)[reply]

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