Time Series: Decomposition Theory (TS E3)

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Time series can be broken down into components for modeling and understanding purposes. These are typically trend, cycle, and season as well as the error term. The only difference between cycle and season is the number of cycles that occur over a time period. Cycles are usually annually or longer whereas seasons are usually less than a year. You can also have multiple seasons in one model. This video is going to cover the basic theory behind this decomposition and how they work together to model a time series. Future videos will give examples on how this would work with real data.

TS E1: Business vs Statistical Analytics: Concept Overview

TS E2: Time Series Intro: Stochastic Processes and Structure

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  1. Dimitri Bianco
  2. TS
  3. time series
  4. econometrics
  5. stochastic
  6. process
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Комментарии
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Hey Dimitri, just wanted to show some love and express how much I appreciate your commitment to helping people like me who want to learn this kind of stuff earlier on my own. Thanks so much, really hope you continue to upload!

haonyoass
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Thanks for sharing! It's helpful for me as a Stat student.

datascify
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This is so clear! Thank you for taking the time to make these videos!

xxMikePortnoyJrxx
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Dimitri, I really appreciate these videos with classroom-style material. In this video particularly you introduce a model to be calculated as a product of Trend, Cyclic, and seasonal variables. Why do we consider the model to be a product of variable rather than a sum or some other relationship. Is it a key distinction? Does it matter that's its multiplicative or could an argument be made for additive variables instead?

besapre
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Did you ever think to become a professor? You are very good at explaining, actually I can understand much better you explaining a new topic in ENGLISH than professors explaining topics I already know in ITALIAN

andresrossi