<?xml version='1.0' encoding='UTF-8'?><?xml-stylesheet href="http://www.blogger.com/styles/atom.css" type="text/css"?><feed xmlns='http://www.w3.org/2005/Atom' xmlns:openSearch='http://a9.com/-/spec/opensearchrss/1.0/' xmlns:gd="http://schemas.google.com/g/2005"><id>tag:blogger.com,1999:blog-7958828565254404797.post8673571950771927856..comments</id><updated>2024-11-22T00:46:41.653-08:00</updated><title type='text'>Comments on ListenData: SAS: Time Series Forecasting - ARIMA [Part 3]</title><link rel='http://schemas.google.com/g/2005#feed' type='application/atom+xml' href='https://www.listendata.com/feeds/comments/default'/><link rel='self' type='application/atom+xml' href='https://www.blogger.com/feeds/7958828565254404797/8673571950771927856/comments/default'/><link rel='alternate' type='text/html' href='https://www.listendata.com/2015/09/time-series-forecasting-arima-part-3.html'/><link rel="hub" href="http://pubsubhubbub.appspot.com/"/><author><name>Deepanshu Bhalla</name><uri>http://www.blogger.com/profile/09802839558125192674</uri><email>noreply@blogger.com</email><gd:image rel='http://schemas.google.com/g/2005#thumbnail' width='32' height='32' src='//blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiXm_iOrXFR9Ls-mjtOci4qd1m1V1TXkkWJINuMy84-Axo5pNS6CG7oKwR7hfHHI3tB1yuz8W_qo9HK2Cw5fHfe_4cL_2DCf_LyoK9LMLicZojbNYgypIP-RXNsw1GsVhk/s100/pic.jpg'/></author><generator version='7.00' uri='http://www.blogger.com'>Blogger</generator><openSearch:totalResults>8</openSearch:totalResults><openSearch:startIndex>1</openSearch:startIndex><openSearch:itemsPerPage>25</openSearch:itemsPerPage><entry><id>tag:blogger.com,1999:blog-7958828565254404797.post-8595549223042392050</id><published>2020-03-21T11:23:17.765-07:00</published><updated>2020-03-21T11:23:17.765-07:00</updated><title type='text'>When I run this on my data, the model with the low...</title><content type='html'>When I run this on my data, the model with the lowest MINIC value was not the model with the lowest MAPE value. In this situation which would you pick? Ideally should the same model have the lowest MINIC and MAPE value?</content><link rel='edit' type='application/atom+xml' href='https://www.blogger.com/feeds/7958828565254404797/8673571950771927856/comments/default/8595549223042392050'/><link rel='self' type='application/atom+xml' href='https://www.blogger.com/feeds/7958828565254404797/8673571950771927856/comments/default/8595549223042392050'/><link rel='alternate' type='text/html' href='https://www.listendata.com/2015/09/time-series-forecasting-arima-part-3.html?showComment=1584814997765#c8595549223042392050' title=''/><author><name>Anonymous</name><email>noreply@blogger.com</email><gd:image rel='http://schemas.google.com/g/2005#thumbnail' width='16' height='16' src='https://img1.blogblog.com/img/blank.gif'/></author><thr:in-reply-to xmlns:thr='http://purl.org/syndication/thread/1.0' href='https://www.listendata.com/2015/09/time-series-forecasting-arima-part-3.html' ref='tag:blogger.com,1999:blog-7958828565254404797.post-8673571950771927856' source='http://www.blogger.com/feeds/7958828565254404797/posts/default/8673571950771927856' type='text/html'/><gd:extendedProperty name="blogger.itemClass" value="pid-6939909"/><gd:extendedProperty name="blogger.displayTime" value="March 21, 2020 at 11:23 AM"/></entry><entry><id>tag:blogger.com,1999:blog-7958828565254404797.post-2887661253104014586</id><published>2018-04-05T07:53:31.097-07:00</published><updated>2018-04-05T07:53:31.097-07:00</updated><title type='text'>Hi, a typo here that the MAPE should be mean ABSOL...</title><content type='html'>Hi, a typo here that the MAPE should be mean ABSOLUTE percentage error, not SQUAREd.</content><link rel='edit' type='application/atom+xml' href='https://www.blogger.com/feeds/7958828565254404797/8673571950771927856/comments/default/2887661253104014586'/><link rel='self' type='application/atom+xml' href='https://www.blogger.com/feeds/7958828565254404797/8673571950771927856/comments/default/2887661253104014586'/><link rel='alternate' type='text/html' href='https://www.listendata.com/2015/09/time-series-forecasting-arima-part-3.html?showComment=1522940011097#c2887661253104014586' title=''/><author><name>Anonymous</name><email>noreply@blogger.com</email><gd:image rel='http://schemas.google.com/g/2005#thumbnail' width='16' height='16' src='https://img1.blogblog.com/img/blank.gif'/></author><thr:in-reply-to xmlns:thr='http://purl.org/syndication/thread/1.0' href='https://www.listendata.com/2015/09/time-series-forecasting-arima-part-3.html' ref='tag:blogger.com,1999:blog-7958828565254404797.post-8673571950771927856' source='http://www.blogger.com/feeds/7958828565254404797/posts/default/8673571950771927856' type='text/html'/><gd:extendedProperty name="blogger.itemClass" value="pid-6939909"/><gd:extendedProperty name="blogger.displayTime" value="April 5, 2018 at 7:53 AM"/></entry><entry><id>tag:blogger.com,1999:blog-7958828565254404797.post-922960517898944735</id><published>2017-05-14T23:48:35.874-07:00</published><updated>2017-05-14T23:48:35.874-07:00</updated><title type='text'>Hi...
Really nice. so elaborately explained ARIMA....</title><content type='html'>Hi...<br />Really nice. so elaborately explained ARIMA.appreciate your work..<br /><br />I have a small doubt,if i change my testing or validation data my MAPE will get changed ,So is there any way to make sure that my final model is consistent ..???<br /><br />and also if you have any knowledge on ARIMAX (x-any additional variable,say macroeconomic variable ) and if you can share any example on that i would really appreciate that.. <br /></content><link rel='edit' type='application/atom+xml' href='https://www.blogger.com/feeds/7958828565254404797/8673571950771927856/comments/default/922960517898944735'/><link rel='self' type='application/atom+xml' href='https://www.blogger.com/feeds/7958828565254404797/8673571950771927856/comments/default/922960517898944735'/><link rel='alternate' type='text/html' href='https://www.listendata.com/2015/09/time-series-forecasting-arima-part-3.html?showComment=1494830915874#c922960517898944735' title=''/><author><name>Anonymous</name><uri>https://www.blogger.com/profile/03091547242431938963</uri><email>noreply@blogger.com</email><gd:image rel='http://schemas.google.com/g/2005#thumbnail' width='16' height='16' src='https://img1.blogblog.com/img/b16-rounded.gif'/></author><thr:in-reply-to xmlns:thr='http://purl.org/syndication/thread/1.0' href='https://www.listendata.com/2015/09/time-series-forecasting-arima-part-3.html' ref='tag:blogger.com,1999:blog-7958828565254404797.post-8673571950771927856' source='http://www.blogger.com/feeds/7958828565254404797/posts/default/8673571950771927856' type='text/html'/><gd:extendedProperty name="blogger.itemClass" value="pid-1905954138"/><gd:extendedProperty name="blogger.displayTime" value="May 14, 2017 at 11:48 PM"/></entry><entry><id>tag:blogger.com,1999:blog-7958828565254404797.post-3660201778448626266</id><published>2016-11-28T00:21:09.838-08:00</published><updated>2016-11-28T00:21:09.838-08:00</updated><title type='text'>very nice article....</title><content type='html'>very nice article....</content><link rel='edit' type='application/atom+xml' href='https://www.blogger.com/feeds/7958828565254404797/8673571950771927856/comments/default/3660201778448626266'/><link rel='self' type='application/atom+xml' href='https://www.blogger.com/feeds/7958828565254404797/8673571950771927856/comments/default/3660201778448626266'/><link rel='alternate' type='text/html' href='https://www.listendata.com/2015/09/time-series-forecasting-arima-part-3.html?showComment=1480321269838#c3660201778448626266' title=''/><author><name>sathya</name><uri>https://www.blogger.com/profile/13191226659928934311</uri><email>noreply@blogger.com</email><gd:image rel='http://schemas.google.com/g/2005#thumbnail' width='16' height='16' src='https://img1.blogblog.com/img/b16-rounded.gif'/></author><thr:in-reply-to xmlns:thr='http://purl.org/syndication/thread/1.0' href='https://www.listendata.com/2015/09/time-series-forecasting-arima-part-3.html' ref='tag:blogger.com,1999:blog-7958828565254404797.post-8673571950771927856' source='http://www.blogger.com/feeds/7958828565254404797/posts/default/8673571950771927856' type='text/html'/><gd:extendedProperty name="blogger.itemClass" value="pid-1193741146"/><gd:extendedProperty name="blogger.displayTime" value="November 28, 2016 at 12:21 AM"/></entry><entry><id>tag:blogger.com,1999:blog-7958828565254404797.post-4763112900358832811</id><published>2016-06-30T01:30:05.346-07:00</published><updated>2016-06-30T01:30:05.346-07:00</updated><title type='text'>You do not lose the sequence of the data. First 70...</title><content type='html'>You do not lose the sequence of the data. First 70-80% data-set works as a training set and the rest for validation.</content><link rel='edit' type='application/atom+xml' href='https://www.blogger.com/feeds/7958828565254404797/8673571950771927856/comments/default/4763112900358832811'/><link rel='self' type='application/atom+xml' href='https://www.blogger.com/feeds/7958828565254404797/8673571950771927856/comments/default/4763112900358832811'/><link rel='alternate' type='text/html' href='https://www.listendata.com/2015/09/time-series-forecasting-arima-part-3.html?showComment=1467275405346#c4763112900358832811' title=''/><link rel='related' type='application/atom+xml' href='https://www.blogger.com/feeds/7958828565254404797/8673571950771927856/comments/default/3323429290408167455'/><author><name>Anonymous</name><email>noreply@blogger.com</email><gd:image rel='http://schemas.google.com/g/2005#thumbnail' width='16' height='16' src='https://img1.blogblog.com/img/blank.gif'/></author><thr:in-reply-to xmlns:thr='http://purl.org/syndication/thread/1.0' href='https://www.listendata.com/2015/09/time-series-forecasting-arima-part-3.html' ref='tag:blogger.com,1999:blog-7958828565254404797.post-8673571950771927856' source='http://www.blogger.com/feeds/7958828565254404797/posts/default/8673571950771927856' type='text/html'/><gd:extendedProperty name="blogger.itemClass" value="pid-6939909"/><gd:extendedProperty name="blogger.displayTime" value="June 30, 2016 at 1:30 AM"/></entry><entry><id>tag:blogger.com,1999:blog-7958828565254404797.post-3323429290408167455</id><published>2015-11-20T08:49:24.798-08:00</published><updated>2015-11-20T08:49:24.798-08:00</updated><title type='text'>Hi,

Thank you that u r so elaborately explaining ...</title><content type='html'>Hi,<br /><br />Thank you that u r so elaborately explaining ARIMA.<br /><br />I have a doubt after reading this article.How can we divide the data set into validation and training data while doing so we lose sequence of time series. <br /> </content><link rel='edit' type='application/atom+xml' href='https://www.blogger.com/feeds/7958828565254404797/8673571950771927856/comments/default/3323429290408167455'/><link rel='self' type='application/atom+xml' href='https://www.blogger.com/feeds/7958828565254404797/8673571950771927856/comments/default/3323429290408167455'/><link rel='alternate' type='text/html' href='https://www.listendata.com/2015/09/time-series-forecasting-arima-part-3.html?showComment=1448038164798#c3323429290408167455' title=''/><author><name>Anonymous</name><uri>https://www.blogger.com/profile/02446700855883124538</uri><email>noreply@blogger.com</email><gd:image rel='http://schemas.google.com/g/2005#thumbnail' width='16' height='16' src='https://img1.blogblog.com/img/b16-rounded.gif'/></author><thr:in-reply-to xmlns:thr='http://purl.org/syndication/thread/1.0' href='https://www.listendata.com/2015/09/time-series-forecasting-arima-part-3.html' ref='tag:blogger.com,1999:blog-7958828565254404797.post-8673571950771927856' source='http://www.blogger.com/feeds/7958828565254404797/posts/default/8673571950771927856' type='text/html'/><gd:extendedProperty name="blogger.itemClass" value="pid-1469705553"/><gd:extendedProperty name="blogger.displayTime" value="November 20, 2015 at 8:49 AM"/></entry><entry><id>tag:blogger.com,1999:blog-7958828565254404797.post-6886948153001106390</id><published>2015-09-27T21:10:52.849-07:00</published><updated>2015-09-27T21:10:52.849-07:00</updated><title type='text'>in stead of using Forecast lead=12, you can use a ...</title><content type='html'>in stead of using Forecast lead=12, you can use a higher number in lead option to forecast further.</content><link rel='edit' type='application/atom+xml' href='https://www.blogger.com/feeds/7958828565254404797/8673571950771927856/comments/default/6886948153001106390'/><link rel='self' type='application/atom+xml' href='https://www.blogger.com/feeds/7958828565254404797/8673571950771927856/comments/default/6886948153001106390'/><link rel='alternate' type='text/html' href='https://www.listendata.com/2015/09/time-series-forecasting-arima-part-3.html?showComment=1443413452849#c6886948153001106390' title=''/><author><name>Rajat</name><uri>https://www.blogger.com/profile/03865402448429988208</uri><email>noreply@blogger.com</email><gd:image rel='http://schemas.google.com/g/2005#thumbnail' width='16' height='16' src='https://img1.blogblog.com/img/b16-rounded.gif'/></author><thr:in-reply-to xmlns:thr='http://purl.org/syndication/thread/1.0' href='https://www.listendata.com/2015/09/time-series-forecasting-arima-part-3.html' ref='tag:blogger.com,1999:blog-7958828565254404797.post-8673571950771927856' source='http://www.blogger.com/feeds/7958828565254404797/posts/default/8673571950771927856' type='text/html'/><gd:extendedProperty name="blogger.itemClass" value="pid-2117561144"/><gd:extendedProperty name="blogger.displayTime" value="September 27, 2015 at 9:10 PM"/></entry><entry><id>tag:blogger.com,1999:blog-7958828565254404797.post-6878455765838511287</id><published>2015-09-13T22:16:01.856-07:00</published><updated>2015-09-13T22:16:01.856-07:00</updated><title type='text'>Hi,

Thank your for the detailed explanation of th...</title><content type='html'>Hi,<br /><br />Thank your for the detailed explanation of the Time Series Forecasting model, it&#39;s really helpful.<br /><br />Could you please also elaborate, after selecting the model with the least MAPE, how would we predict the value for the next time period i.e. Jan 61.</content><link rel='edit' type='application/atom+xml' href='https://www.blogger.com/feeds/7958828565254404797/8673571950771927856/comments/default/6878455765838511287'/><link rel='self' type='application/atom+xml' href='https://www.blogger.com/feeds/7958828565254404797/8673571950771927856/comments/default/6878455765838511287'/><link rel='alternate' type='text/html' href='https://www.listendata.com/2015/09/time-series-forecasting-arima-part-3.html?showComment=1442207761856#c6878455765838511287' title=''/><author><name>Anonymous</name><uri>https://www.blogger.com/profile/11690827674817634491</uri><email>noreply@blogger.com</email><gd:image rel='http://schemas.google.com/g/2005#thumbnail' width='16' height='16' src='https://img1.blogblog.com/img/b16-rounded.gif'/></author><thr:in-reply-to xmlns:thr='http://purl.org/syndication/thread/1.0' href='https://www.listendata.com/2015/09/time-series-forecasting-arima-part-3.html' ref='tag:blogger.com,1999:blog-7958828565254404797.post-8673571950771927856' source='http://www.blogger.com/feeds/7958828565254404797/posts/default/8673571950771927856' type='text/html'/><gd:extendedProperty name="blogger.itemClass" value="pid-1527249048"/><gd:extendedProperty name="blogger.displayTime" value="September 13, 2015 at 10:16 PM"/></entry></feed>