Weather Forecasting using ARIMA & SARIMA Model

Identifying order AR(p), I(d), MA(q)

Learning Outcome

5

Build a forecasting workflow

 

4

Interpret ACF & PACF plots

3

Test stationarity

2

Identify p, d, q parameters

1

Understand ARIMA components

Quick Recall

Neural Networks

Loss Functions

Optimization Techniques

Those models learn relationships in features

Today we learn models for sequential data

An airline wants to forecast how many passengers will travel next month.

Challenges:

Changing trends

Seasonal variations

Random fluctuations

How Machines Solve This:

They analyze patterns from past data:

Previous passenger values

Trend changes over time

Error patterns

Solution:

Use the ARIMA Model for forecasting

What is ARIMA?

AutoRegressive Integrated Moving Average

Model format

ARIMA(p, d, q)

Components Overview

p

AR order

Controls past value influence

Controls trend removal

Controls error adjustment

d (Differencing)

q (MA order)

Identification Workflow

How to Find (p, d, q)

Step-by-Step:

Stationarity Concept

Key Properties:

Constant mean

Constant variance

No long-term trend

Detecting Stationarity

Augmented Dickey Fuller test

Decision rule:

  • p-value < 0.05 → Stationary
  • p-value > 0.05 → Non-stationary

Differencing

Removing Trend

Repeat Until Stationary

Apply differencing operations until the time series becomes stationary. Number of operations = d parameter.

Understanding Autocorrelation

Correlation Between Lags

Key Concept :

Time Series values depends on past values. 

Autocorrelation Measures

  • ACF : Total correlation (Direct + indirect)
  • PACF : Direct correlation only

Today's value correlated with yesterday's value, which correlates with the day before, and so on.

PACF Plot

Summary

5

Auto ARIMA simplifies modeling

4

ACF identifies MA(q)

3

PACF identifies AR(p)

2

d determined by stationarity

1

ARIMA models forecast time series

Quiz

Which plot helps determine AR(p) order?

A. ACF

B. PACF

C. ADF Test

D. Differencing

Quiz-Answer

Which plot helps determine AR(p) order?

A. ACF

B. PACF

C. ADF Test

D. Differencing

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