Why an MA(1) model is the same thing as an AR(∞) model
Пікірлер: 71
@yesbay1852 жыл бұрын
This is in fact a beautiful use of the operator theory, thank you for the video
@somethingness Жыл бұрын
This was illuminating (and fun!) You are a *great* teacher!
@ritvikmath Жыл бұрын
Thanks!
@deepak_kori7 ай бұрын
Let's imagine you have a toy car that you play with daily. How you play with the car one day might affect how you play with it the next day. Now, imagine if we wanted to predict how you'll play with the car tomorrow based on how you played with it in the past. An AR(∞) model is like trying to predict how you'll play with the car tomorrow by looking at every single way you played with it in the past, even going back forever! But that's impossible because we can't remember or keep track of how you've played with the car since birth. So, it's like having too much information to deal with. On the other hand, an MA(1) model is more straightforward. It only looks at how you played with the car yesterday and uses that to guess how you might play with it tomorrow. It's like saying, "Hey, since you played with the car this way yesterday, you might play with it in a similar way tomorrow." It's easier to work with because it only focuses on the most recent way you played with the car, not all the ways from the past.
@teegnas4 жыл бұрын
I see a recommendation for his channel and that too on Time Series, I click PLAY!
@pipertripp6 ай бұрын
Very helpful. I'm working through and online course on time series and you playlist is going to be an excellent supplement to the course content. Thank you!!
@cynthpielin73342 жыл бұрын
The causal diagram was just too good!
@teresanuvoloni42144 жыл бұрын
your videos are amazing!!! THANK YOU SO MUCH!!
@NoorFatima-je4ou Жыл бұрын
YOU HAVE SAVED MY DEGREE THANK YOU FOR YOUR VIDEOS ON TIME SERIES ANALYSIS
@sukhwindersingh92684 ай бұрын
He is too innovative, I watched every video more than once
@gooeyyeoog85353 ай бұрын
please keep it up, I wish you'd re-organized the playlist for us to follow
@soldierkitvictor2 жыл бұрын
great video! just wondering why we dont need to input "miu" in the MA1 model, which was shown in the "Time Series Talk:Moving average Model" video? Thanks!
@BetoAlvesRocha Жыл бұрын
I was struggling with the same here and I think it would be great if this was explained in the video. I think for a matter of simplicity, they just considered mu = 0.
@timurtenishev6243 Жыл бұрын
thank you very much, I love your playlist on time series. wonderful explanations!!!
@nehasht23 жыл бұрын
It's so cool..... I was able to guess in the end it was AR model before you said.... How ur videos are relatable ... awesome
@ritvikmath3 жыл бұрын
thanks!
@drmearajuddin23344 жыл бұрын
Sir plzz make a detailed video on cointegration.. Especially Johensen cointegration...
@misevero6 ай бұрын
@rivikmath that was sooooo clear. thank you!
@gtc47732 жыл бұрын
thank you my friend, you're the best
@reconnectortylerjoejoe9409 Жыл бұрын
wonderful job!!!!!!!omg i love you
@elvitd6704 Жыл бұрын
you are the best of the best
@gregoryyampolsky557 Жыл бұрын
omg thank you for making this make sense to me
@Glassful3 жыл бұрын
So we are sayin because of invertibility we don't have to figure out error terms and use lagged value of actual time series itself. Brilliant!
@Alex-sy4gg3 ай бұрын
briliant vid !!!
@ari.in_media_res3 жыл бұрын
Brilliant!
@lukasschipper98313 жыл бұрын
Thank you very much!
@ritvikmath3 жыл бұрын
You're welcome!
@kenyoon27693 жыл бұрын
Thank you for your great video!
@ritvikmath3 жыл бұрын
My pleasure!
@mansikumari49543 жыл бұрын
Outstanding!!
@jihoonkang38472 жыл бұрын
Thanks for the videos. I am really enjoying studying these concepts from your playlists. Just a short comment. From MA1 model, C_1 = - phi * e_0 + e_1, so, e_2 = C_2 + phi * e_1 = C_2 + phi * C_1 + phi^2 * e_0. Propagation gives e_n = C_n + phi * C_n-1 + phi^2 * C_n-2 * phi^3 * C_n-3 + ... + phi^n * e_0. When n is large enough and phi < 1, the last term goes to 0 and Cn is expressed as the sum of the past C_n-k series.
@tumellomotabola62682 жыл бұрын
Thank You
@Fernandinh002 жыл бұрын
What a great explanation! Congrats
@thirdreplicator2 жыл бұрын
It would be nice to have at the end of each video a homework data set and a list of two or three questions.
@fatimajunejo3960 Жыл бұрын
Pure genius
@user-nf6jl9cg1t4 ай бұрын
What doesn't work out for me is saying that eps_t is a function of C_t, because eps_t is supposed to be white noise right?
@taramorovatdar37104 жыл бұрын
I love your videos they are really helpful. Thank you so much
@gabri99grisel4 жыл бұрын
The best explanation ever! Thanks
@donleitoso93224 жыл бұрын
Hi, there! I assist the students of a Time Series Econometrics course in college. Found this video while preparing a revision lesson. Pretty good!
@qiguosun1292 жыл бұрын
Cool!
@tangt3043 жыл бұрын
Excellent explanation! Thank you!
@mananthakkar70752 жыл бұрын
Awesome
@edoson01 Жыл бұрын
I think it can be much more intuitively illustrated by simply changing the subject of the equation. Instead of Ct = ... you formalize it as EPSt = ..., and recursively plug in the corresponding formula.
@DM-py7pj10 ай бұрын
1:50 can you use phi and theta interchangeably when referring to an MA process? In other videos you used theta only for MA
@hameddadgour2 жыл бұрын
Great presentation!
@realcirno17502 жыл бұрын
damn... this goes hard
@user-vm9hl3gl5h Жыл бұрын
The arrow in the left diagram is more like a "function of", instead of "caused by".
@alastairperumal92573 жыл бұрын
@ritvikmath Just a question: how do we prove that the absolute value of Phi is less than one? or is this given?
@user-sr4qn6mu1v Жыл бұрын
Very clear!
@koeunlee83263 жыл бұрын
I really miss your old video format with the white board only. Can I ask why you changed it?
@summortal86202 жыл бұрын
Tysm for the helpfull vids! I have question, in your Lag Operator video, you rewrite the ARMA in terms of lag operator by (phi1Lyt + phi2L^2yt+...+phi3kL^kyt), but in this video you square the phi's as well. why is it different? thnx in advance, Greetings
@archer93222 жыл бұрын
You are a hero.🤣
@yybg1004 жыл бұрын
Can you help around the logic of why ma(1) processes donot follow Markov property
@urisbdbcn4 жыл бұрын
Good work, sir.
@MinhNguyen-tv7ph5 ай бұрын
Bro you save my ass again!
@totochandelier4 жыл бұрын
you 're great thx
@karunamayiholisticinc2 жыл бұрын
Hi Ritvikmath, I was wondering if you give tutoring lessons in Mathematics for Data Science?
@ddp47753 жыл бұрын
That's cool.
@vandanaarya4313 жыл бұрын
H do we solve this equation: v[k[=e[k]+1.4e[k-1]+0.38e[k-2]???
@jayjayf96993 жыл бұрын
Why have u omitted the mean in the MA(1) model?
@dianas.53514 жыл бұрын
Thank you so much for the video! I am rewatching it because I indeed have trouble understanding this topic :D I have a question: Why do you use the coefficient Phi for the MA-process? In my textbook, we use this letter for the AR-process, and for the MA-process we use the letter Theta. Or is that not so important?
@Codrean4 жыл бұрын
You're right, but it is just notation. I'm actually facing this problem because every book or video I read/watch has a different notation, slowing the learning process.
@roeiohayon45014 жыл бұрын
Hi, I was wondering how invertability useful - what can I do with that information
@vicentegabrielscalisi61822 жыл бұрын
Ya le errás aquí. Tenés que preparar mejor estos temas. Thanks 🌹🌹
@chenjus3 жыл бұрын
When I look at that causal diagram, all I see is a RNN
@drmearajuddin23344 жыл бұрын
Sir why we put log operator on time series variables like log gdp log cpi log oil price... What is the benefit of putting log.. Plzz answer sir
@5astelija754 жыл бұрын
Exponential time-series cannot be studied properly. Logging them removes the exponentiality