Introduction of Valuable time Combination of Projecting | Step 7 (seven) | ARIMA Forecasting real life Example in R

Introduction of Time Series Forecasting | Part 7 | ARIMA Forecasting real life Example in R

Hi guys.. in this part 6 of time series forecasting video series I have taken a real life example of rain fall in india and predicted the future years rains with by producing the arima model and then using the forecast package, I predicted the next few years rain fall values.

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Eine Antwort auf „Introduction of Valuable time Combination of Projecting | Step 7 (seven) | ARIMA Forecasting real life Example in R“

  1. Great Video.. THanks for sharing the knowledge…..

    The first model(rain_model) that you have run is working on the differentiate series not original series, hence Auto-Arima result is different , since the original series was already stationary. While selecting p & q values from PACF and ACF, respectively, you have followed a different approach to count value for p and q. For PACF, you have counted lag 0 as also…What is the reason for that?

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