{"action":"created","issue":{"url":"https://api.github.com/repos/statsmodels/statsmodels/issues/4688","repository_url":"https://api.github.com/repos/statsmodels/statsmodels","labels_url":"https://api.github.com/repos/statsmodels/statsmodels/issues/4688/labels{/name}","comments_url":"https://api.github.com/repos/statsmodels/statsmodels/issues/4688/comments","events_url":"https://api.github.com/repos/statsmodels/statsmodels/issues/4688/events","html_url":"https://github.com/statsmodels/statsmodels/issues/4688","id":326881743,"node_id":"MDU6SXNzdWUzMjY4ODE3NDM=","number":4688,"title":"Trouble finding trend, and seasonality, and cycles with SARIMA","user":{"login":"samuel-1985","id":39685614,"node_id":"MDQ6VXNlcjM5Njg1NjE0","avatar_url":"https://avatars1.githubusercontent.com/u/39685614?v=4","gravatar_id":"","url":"https://api.github.com/users/samuel-1985","html_url":"https://github.com/samuel-1985","followers_url":"https://api.github.com/users/samuel-1985/followers","following_url":"https://api.github.com/users/samuel-1985/following{/other_user}","gists_url":"https://api.github.com/users/samuel-1985/gists{/gist_id}","starred_url":"https://api.github.com/users/samuel-1985/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/samuel-1985/subscriptions","organizations_url":"https://api.github.com/users/samuel-1985/orgs","repos_url":"https://api.github.com/users/samuel-1985/repos","events_url":"https://api.github.com/users/samuel-1985/events{/privacy}","received_events_url":"https://api.github.com/users/samuel-1985/received_events","type":"User","site_admin":false},"labels":[],"state":"closed","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":6,"created_at":"2018-05-28T03:04:43Z","updated_at":"2018-06-13T10:31:52Z","closed_at":"2018-06-04T17:29:00Z","author_association":"NONE","body":"Hi\r\nI am a newbie to this so I already apologize if my questions sound too simple.\r\n\r\nI have a daily time series and want to do daily forecasting that involves irregular seasonal effects or causal variables like holidays. the data should have messy seasonal factors such as day of the month etc., holiday effects, sometimes moving holiday effects (Example: Easter). How can I factor in all these components in SARIMA? Also, how can I not only capture the effect on the holiday but also the effect surrounding that holiday with SARIMA? For instance, people don't shop on New Years day. All the shopping starts at least 2 weeks prior to new years day and ramps down after New Years day. The weeks surrounding the Holiday will be different from a typical week say you observe in a typical week February.\r\nMoreover, if my data is daily data, how can I capture any possible seasonality including weekly, monthly, and annually? Do I do it by multiplicative seasonal components? If yes, how should the command look like?\r\n\r\nPlease advise how my SARIMA function, and its arguments should look like.\r\nRegards\r\nSamuel"},"comment":{"url":"https://api.github.com/repos/statsmodels/statsmodels/issues/comments/396891815","html_url":"https://github.com/statsmodels/statsmodels/issues/4688#issuecomment-396891815","issue_url":"https://api.github.com/repos/statsmodels/statsmodels/issues/4688","id":396891815,"node_id":"MDEyOklzc3VlQ29tbWVudDM5Njg5MTgxNQ==","user":{"login":"REspanha","id":15313917,"node_id":"MDQ6VXNlcjE1MzEzOTE3","avatar_url":"https://avatars0.githubusercontent.com/u/15313917?v=4","gravatar_id":"","url":"https://api.github.com/users/REspanha","html_url":"https://github.com/REspanha","followers_url":"https://api.github.com/users/REspanha/followers","following_url":"https://api.github.com/users/REspanha/following{/other_user}","gists_url":"https://api.github.com/users/REspanha/gists{/gist_id}","starred_url":"https://api.github.com/users/REspanha/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/REspanha/subscriptions","organizations_url":"https://api.github.com/users/REspanha/orgs","repos_url":"https://api.github.com/users/REspanha/repos","events_url":"https://api.github.com/users/REspanha/events{/privacy}","received_events_url":"https://api.github.com/users/REspanha/received_events","type":"User","site_admin":false},"created_at":"2018-06-13T10:31:51Z","updated_at":"2018-06-13T10:31:51Z","author_association":"NONE","body":"Hi Samuel,\r\n\r\nI was having the same problem with ARIMA. In my case I have daily cycles with weekly seasons too. Imagine a number of cars per hour dataset. During the week I have some daily pattern but in the weekend it drops. I was looking for a model to capture multi seasonality and I found TBATS. I gave it a try but no clear success. I ended up using SARIMA with order (5,1,0) and seasonal order (0,1,0,24*7). The 5,1,0 was able to catch the daily cycles by removing the cycle with differencing (1)and the seasonal param m=24*7 captured the second season (weekly). I have pretty good results, however I am not able to induce holidays or specific dates. Maybe exog in SARIMAX that josef suggested. OR.... facebook launched a forecast library called prophet. It has the holidays and multiseasonality features. Give it a try.\r\nhttps://facebook.github.io/prophet/docs/quick_start.html"}}
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