What are some advanced techniques for time series analysis?

What are some advanced techniques for time series analysis?

Some advanced techniques include ARIMA, Seasonal Decomposition, and Long Short-Term Memory (LSTM) networks.

Can you explain how ARIMA works?

ARIMA stands for AutoRegressive Integrated Moving Average. It models time series data by combining autoregression, differencing, and moving averages.

What is Seasonal Decomposition?

Seasonal Decomposition separates a time series into trend, seasonal, and residual components, helping to analyze underlying patterns.

How do LSTM networks improve time series forecasting?

LSTM networks can capture long-term dependencies in data, making them effective for complex time series with non-linear patterns.