Linear Predictive Models

Linear predictive models are tools used to forecast future data points based on past observations by assuming a linear relationship. They estimate the next value by combining previous values with specific weights, effectively capturing patterns like trends or seasonal behaviors. For example, they can predict future stock prices or speech signals by analyzing past data, making them useful in finance, speech processing, and more. The key idea is that the future can be approximated as a weighted sum of recent history, providing a simple yet powerful way to model and anticipate complex sequences.