{"id":1964,"date":"2019-01-22T11:58:29","date_gmt":"2019-01-22T12:58:29","guid":{"rendered":"http:\/\/sites.uac.pt\/amendes\/?p=1964"},"modified":"2019-01-22T11:58:29","modified_gmt":"2019-01-22T12:58:29","slug":"extracting-seasonality-and-trend-from-data-decomposition-using-r","status":"publish","type":"post","link":"https:\/\/sites.uac.pt\/amendes\/estatistica\/extracting-seasonality-and-trend-from-data-decomposition-using-r\/","title":{"rendered":"Extracting Seasonality and Trend from Data: Decomposition Using R"},"content":{"rendered":"
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Uma excelente descri\u00e7\u00e3o da decomposi\u00e7\u00e3o cl\u00e1ssica com Python e R.<\/span><\/p>\n

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Time series decomposition works by splitting a time series into three components: seasonality, trends and random fluctiation. To show how this works, we will study\u00a0the decompose( ) and STL( ) functions in the R language<\/a>.
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Understanding Decomposition<\/h2>\n<\/div>\n<\/div>\n
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Decompose One Time Series into Multiple Series<\/h4>\n

Time series decomposition is a mathematical\u00a0procedure which transforms a time series into multiple different time series.\u00a0The original time series is often split into 3 component series:<\/p>\n

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  • Seasonal:<\/strong> Patterns that repeat with a fixed period of time. For example, a website might receive more visits during weekends; this would produce data with a seasonality of 7 days.<\/li>\n
  • Trend:<\/strong> The underlying trend of the metrics. A website increasing in popularity should show a general trend that goes up.<\/li>\n
  • Random:<\/strong> Also call \u201cnoise\u201d, \u201cirregular\u201d or \u201cremainder,\u201d this is the\u00a0residuals of the original time series\u00a0after the seasonal and trend series are removed.<\/li>\n<\/ul>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

    Uma excelente descri\u00e7\u00e3o da decomposi\u00e7\u00e3o cl\u00e1ssica com Python e R. Time series decomposition works by splitting a time series into three components: seasonality, trends and random fluctiation. To show how this works, we will study\u00a0the decompose( ) and STL( ) functions in the R language. Understanding Decomposition Decompose One Time Series into Multiple Series Time […]<\/p>\n","protected":false},"author":159,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"categories":[102,109,190,194,105,150],"tags":[193,121,114,120],"class_list":["post-1964","post","type-post","status-publish","format-standard","hentry","category-estatistica","category-investigacao-operacional","category-licoes","category-linguagens-de-programacao","category-materiais-ensino","category-materiais-para-profissionais","tag-engenharia","tag-inferencia","tag-optimizacao","tag-previsao"],"_links":{"self":[{"href":"https:\/\/sites.uac.pt\/amendes\/wp-json\/wp\/v2\/posts\/1964","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/sites.uac.pt\/amendes\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/sites.uac.pt\/amendes\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/sites.uac.pt\/amendes\/wp-json\/wp\/v2\/users\/159"}],"replies":[{"embeddable":true,"href":"https:\/\/sites.uac.pt\/amendes\/wp-json\/wp\/v2\/comments?post=1964"}],"version-history":[{"count":1,"href":"https:\/\/sites.uac.pt\/amendes\/wp-json\/wp\/v2\/posts\/1964\/revisions"}],"predecessor-version":[{"id":1966,"href":"https:\/\/sites.uac.pt\/amendes\/wp-json\/wp\/v2\/posts\/1964\/revisions\/1966"}],"wp:attachment":[{"href":"https:\/\/sites.uac.pt\/amendes\/wp-json\/wp\/v2\/media?parent=1964"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/sites.uac.pt\/amendes\/wp-json\/wp\/v2\/categories?post=1964"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/sites.uac.pt\/amendes\/wp-json\/wp\/v2\/tags?post=1964"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}