Forecasting the Future with ARMA (Autoregressive Moving Average Models)

Sairam K
kgxperience
Published in
3 min readJul 2, 2023

Soo Humoon…..Tech Prose : Words Unleashed..🤖🔥

Then…Let’s start something about Machine Learning…

This Humoon is not going to bore up the readers with all basics and blah blah roadmaps and other regular stuffs over Machine Learning

Lets start up our knowledge development flow with an quick understanding over Unsupervised Learning ,TSA and an interesting concept on forecasting………..🔥🔥

So, Our Knowledge development path goes up interesting from now with some base and some interesting concept over the topics on ML…

Unsupervised Learning

#Common Internet Stuff

The main goal over here is to uncover patterns, structures, or relationships in data without explicit guidance or labeled examples

So the way defines just to make some useful insights over an unlabeled data’s..

Let’s jump quickly over to ARMA

Autoregressive Moving Average Models

So the stuff is ..

A Popular approach for time series forecasting is the Autoregressive Moving Average (ARMA) model.

Combining elements of autoregressive (AR) and moving average (MA) models

AR — linear regression model that predicts future values based on past values.

MA — predicts future values based on the errors of past predictions

Soooo..To strong up the TSA analysis…

ARMA models use past observations and the estimated parameters to forecast the next value in the time series. The forecasts are accompanied by prediction intervals that provide a measure of uncertainty around the point estimates.

The ARMA model is specified by two parameters: p and q. The p parameter indicates the number of AR terms in the model, and the q parameter indicates the number of MA terms in the model.

Simple Flow..

To forecast using ARMA, you first need to estimate the parameters of the model.

This can be done using a variety of methods, such as maximum likelihood estimation or least squares estimation.

Once the parameters have been estimated, you can use the model to forecast future values.

The forecast is simply the predicted value of the time series at a future time.

ARMA forecasting is a relatively simple and straightforward method. It is often used for short-term forecasting, such as forecasting demand for a product or service.

blah blah blah….ufff.😮‍💨😮‍💨

Let’s stop with it….The gist over the concept is delivered..more Knowledge will be poured soon…🔥🔥

Let’s Strengthen up the Humoon..🔥🔥🤖🤖

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Hence the Humoon …. Sairam K ..

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Sairam K
kgxperience

Humoon..Talks about Machine Learning,Data Science,AI Tools...