<?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.post3749966077903675288..comments</id><updated>2024-11-22T00:46:41.653-08:00</updated><title type='text'>Comments on ListenData: Time Series Forecasting - ARIMA [Part 1]</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/7958828565254404797/3749966077903675288/comments/default'/><link rel='alternate' type='text/html' href='https://www.listendata.com/2015/08/time-series-forecasting-arima-part-1.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>4</openSearch:totalResults><openSearch:startIndex>1</openSearch:startIndex><openSearch:itemsPerPage>25</openSearch:itemsPerPage><entry><id>tag:blogger.com,1999:blog-7958828565254404797.post-6435042149000555482</id><published>2017-06-11T05:57:15.707-07:00</published><updated>2017-06-11T05:57:15.707-07:00</updated><title type='text'>Hi Rishabh,&#xa;&#xa;I believe that for white noise, at an...</title><content type='html'>Hi Rishabh,&lt;br /&gt;&lt;br /&gt;I believe that for white noise, at any instant the probability associated with the occurence of any particular value is 0. Further, each value is indepedent of the others. These justify the fact that overall, the mean value of white noise is zero and therefore a constant.&lt;br /&gt;&lt;br /&gt;For a mathematical explanation,the definition of a white series is that the covariance matrix should be an identity matrix(I).&lt;br /&gt;&lt;br /&gt;Let x be a random vector. Covariance matrix of a random vector is E{x*x&amp;#39;}. Mean of the random vector is m = E{x}. Let y be a white random&lt;br /&gt;vector with zero mean so that x = y + m.&lt;br /&gt;&lt;br /&gt;Now,&lt;br /&gt;E{x*x&amp;#39;} = E{(y+m)*(y&amp;#39;+m&amp;#39;)} = E{y*y&amp;#39;}+E{y*m&amp;#39;}+E{m*y&amp;#39;}+E{m*m&amp;#39;} = I + E{y}*m&amp;#39; + m*E{y&amp;#39;} + m*m&amp;#39; = I + m*m&amp;#39;.&lt;br /&gt;Clearly, for x to be white series,&lt;br /&gt;(I + m*m&amp;#39;) should be equal to I =&amp;gt; random vector is not white if the mean is not zero.&lt;br /&gt;&lt;br /&gt;Hope this helps :)</content><link rel='edit' type='application/atom+xml' href='https://www.blogger.com/feeds/7958828565254404797/3749966077903675288/comments/default/6435042149000555482'/><link rel='self' type='application/atom+xml' href='https://www.blogger.com/feeds/7958828565254404797/3749966077903675288/comments/default/6435042149000555482'/><link rel='alternate' type='text/html' href='https://www.listendata.com/2015/08/time-series-forecasting-arima-part-1.html?showComment=1497185835707#c6435042149000555482' title=''/><link rel='related' type='application/atom+xml' href='https://www.blogger.com/feeds/7958828565254404797/3749966077903675288/comments/default/3879184779120759937'/><author><name>Arko</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/2015/08/time-series-forecasting-arima-part-1.html' ref='tag:blogger.com,1999:blog-7958828565254404797.post-3749966077903675288' source='http://www.blogger.com/feeds/7958828565254404797/posts/default/3749966077903675288' type='text/html'/><gd:extendedProperty name="blogger.itemClass" value="pid-6939909"/><gd:extendedProperty name="blogger.displayTime" value="June 11, 2017 at 5:57 AM"/></entry><entry><id>tag:blogger.com,1999:blog-7958828565254404797.post-3879184779120759937</id><published>2015-12-02T01:57:26.878-08:00</published><updated>2015-12-02T01:57:26.878-08:00</updated><title type='text'>I am not able to understand that how it can be sta...</title><content type='html'>I am not able to understand that how it can be stationary if it has sudden jumps or erratic changes</content><link rel='edit' type='application/atom+xml' href='https://www.blogger.com/feeds/7958828565254404797/3749966077903675288/comments/default/3879184779120759937'/><link rel='self' type='application/atom+xml' href='https://www.blogger.com/feeds/7958828565254404797/3749966077903675288/comments/default/3879184779120759937'/><link rel='alternate' type='text/html' href='https://www.listendata.com/2015/08/time-series-forecasting-arima-part-1.html?showComment=1449050246878#c3879184779120759937' 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/2015/08/time-series-forecasting-arima-part-1.html' ref='tag:blogger.com,1999:blog-7958828565254404797.post-3749966077903675288' source='http://www.blogger.com/feeds/7958828565254404797/posts/default/3749966077903675288' type='text/html'/><gd:extendedProperty name="blogger.itemClass" value="pid-6939909"/><gd:extendedProperty name="blogger.displayTime" value="December 2, 2015 at 1:57 AM"/></entry><entry><id>tag:blogger.com,1999:blog-7958828565254404797.post-8121035875389226036</id><published>2015-12-01T12:09:48.933-08:00</published><updated>2015-12-01T12:09:48.933-08:00</updated><title type='text'>A white noise series has a constant mean (of zero)...</title><content type='html'>A white noise series has a constant mean (of zero), a constant variance and no correlation. Hence, it is stationary. Whereas, random walk is non-stationary as its mean and variance increases over time.</content><link rel='edit' type='application/atom+xml' href='https://www.blogger.com/feeds/7958828565254404797/3749966077903675288/comments/default/8121035875389226036'/><link rel='self' type='application/atom+xml' href='https://www.blogger.com/feeds/7958828565254404797/3749966077903675288/comments/default/8121035875389226036'/><link rel='alternate' type='text/html' href='https://www.listendata.com/2015/08/time-series-forecasting-arima-part-1.html?showComment=1449000588933#c8121035875389226036' title=''/><link rel='related' type='application/atom+xml' href='https://www.blogger.com/feeds/7958828565254404797/3749966077903675288/comments/default/8017654468148870171'/><author><name>Deepanshu Bhalla</name><uri>https://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><thr:in-reply-to xmlns:thr='http://purl.org/syndication/thread/1.0' href='https://www.listendata.com/2015/08/time-series-forecasting-arima-part-1.html' ref='tag:blogger.com,1999:blog-7958828565254404797.post-3749966077903675288' source='http://www.blogger.com/feeds/7958828565254404797/posts/default/3749966077903675288' type='text/html'/><gd:extendedProperty name="blogger.itemClass" value="pid-966036103"/><gd:extendedProperty name="blogger.displayTime" value="December 1, 2015 at 12:09 PM"/></entry><entry><id>tag:blogger.com,1999:blog-7958828565254404797.post-8017654468148870171</id><published>2015-12-01T05:58:27.729-08:00</published><updated>2015-12-01T05:58:27.729-08:00</updated><title type='text'>HI Folk,&#xa;thanks for providing us a rich article on...</title><content type='html'>HI Folk,&lt;br /&gt;thanks for providing us a rich article on Forecasting,&lt;br /&gt;Could you please elaborate or explain White Noise again,&lt;br /&gt;Definition above for White Noise is ONE WITH CONSTANT MEAN AND VARIATION, by this  I am getting it that both mean and variance are constant.&lt;br /&gt;&lt;br /&gt;But when again in short definition for White noise has been explained in Random Walk  column then things are quite different . It is mentioned that with zero mean and variance one.&lt;br /&gt;&lt;br /&gt;Could you be so kind to explain the thin line of difference between them. </content><link rel='edit' type='application/atom+xml' href='https://www.blogger.com/feeds/7958828565254404797/3749966077903675288/comments/default/8017654468148870171'/><link rel='self' type='application/atom+xml' href='https://www.blogger.com/feeds/7958828565254404797/3749966077903675288/comments/default/8017654468148870171'/><link rel='alternate' type='text/html' href='https://www.listendata.com/2015/08/time-series-forecasting-arima-part-1.html?showComment=1448978307729#c8017654468148870171' 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/2015/08/time-series-forecasting-arima-part-1.html' ref='tag:blogger.com,1999:blog-7958828565254404797.post-3749966077903675288' source='http://www.blogger.com/feeds/7958828565254404797/posts/default/3749966077903675288' type='text/html'/><gd:extendedProperty name="blogger.itemClass" value="pid-6939909"/><gd:extendedProperty name="blogger.displayTime" value="December 1, 2015 at 5:58 AM"/></entry></feed>