{"id":25059,"date":"2024-01-03T08:27:14","date_gmt":"2024-01-03T07:27:14","guid":{"rendered":"https:\/\/www.graviton.at\/letterswaplibrary\/tsa-time-series-analysis-decomposition\/"},"modified":"2024-01-03T08:27:14","modified_gmt":"2024-01-03T07:27:14","slug":"tsa-time-series-analysis-decomposition","status":"publish","type":"post","link":"https:\/\/www.graviton.at\/letterswaplibrary\/tsa-time-series-analysis-decomposition\/","title":{"rendered":"TSA &#8211; Time Series Analysis Decomposition"},"content":{"rendered":"<p><!-- SC_OFF --><\/p>\n<div class=\"md\">\n<p>I am studying a daily dataset from a game which contains informations about the peak of players from 2013-2023. This is my first try applying decomposition to see how time series components behaves. Later I would like to perform a forecasting using some models, I have applied the ADF test and it revealed the series as stationary. I&#8217;m having some questions to determine what value could fit better in the period parammeter with a daily data.<\/p>\n<p>This is the series over the whole time:<br \/> <a href=\"https:\/\/i.stack.imgur.com\/jlsSm.png\">https:\/\/i.stack.imgur.com\/jlsSm.png<\/a><\/p>\n<p>Additive model:<br \/> <a href=\"https:\/\/i.stack.imgur.com\/jlsSm.png\">https:\/\/i.stack.imgur.com\/jlsSm.png<\/a> <\/p>\n<p>Multiplicative model:<br \/> <a href=\"https:\/\/i.stack.imgur.com\/3MAoB.png\">https:\/\/i.stack.imgur.com\/3MAoB.png<\/a><\/p>\n<p>Based on different types of time series data such as annual, monthly and daily, how should the choice of period be made?<\/p>\n<\/div>\n<p><!-- SC_ON -->   submitted by   <a href=\"https:\/\/www.reddit.com\/user\/Dota_curious\"> \/u\/Dota_curious <\/a> <br \/> <span><a href=\"https:\/\/www.reddit.com\/r\/datasets\/comments\/18x24ic\/tsa_time_series_analysis_decomposition\/\">[link]<\/a><\/span>   <span><a href=\"https:\/\/www.reddit.com\/r\/datasets\/comments\/18x24ic\/tsa_time_series_analysis_decomposition\/\">[comments]<\/a><\/span><\/p><div class='watch-action'><div class='watch-position align-right'><div class='action-like'><a class='lbg-style1 like-25059 jlk' href='javascript:void(0)' data-task='like' data-post_id='25059' data-nonce='65e0e39b87' rel='nofollow'><img class='wti-pixel' src='https:\/\/www.graviton.at\/letterswaplibrary\/wp-content\/plugins\/wti-like-post\/images\/pixel.gif' title='Like' \/><span class='lc-25059 lc'>0<\/span><\/a><\/div><\/div> <div class='status-25059 status align-right'><\/div><\/div><div class='wti-clear'><\/div>","protected":false},"excerpt":{"rendered":"<p>I am studying a daily dataset from a game which contains informations about the peak of players&#8230;<\/p>\n","protected":false},"author":0,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[85],"tags":[],"class_list":["post-25059","post","type-post","status-publish","format-standard","hentry","category-datatards","wpcat-85-id"],"_links":{"self":[{"href":"https:\/\/www.graviton.at\/letterswaplibrary\/wp-json\/wp\/v2\/posts\/25059","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.graviton.at\/letterswaplibrary\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.graviton.at\/letterswaplibrary\/wp-json\/wp\/v2\/types\/post"}],"replies":[{"embeddable":true,"href":"https:\/\/www.graviton.at\/letterswaplibrary\/wp-json\/wp\/v2\/comments?post=25059"}],"version-history":[{"count":0,"href":"https:\/\/www.graviton.at\/letterswaplibrary\/wp-json\/wp\/v2\/posts\/25059\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.graviton.at\/letterswaplibrary\/wp-json\/wp\/v2\/media?parent=25059"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.graviton.at\/letterswaplibrary\/wp-json\/wp\/v2\/categories?post=25059"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.graviton.at\/letterswaplibrary\/wp-json\/wp\/v2\/tags?post=25059"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}