Nick Rotella scientist engineer developer

Regression and Recursive Estimation

Up until this point, we’ve kept things pretty abstract. How does solving for the least squares solution relate to estimation? Let’s start with an application you’ve probably used before - fitting a line to some noisy experimental data, also known as linear regression.

Linear Regression

Let’s say you have a bunch of data points in two dimensions (for simplicity, though the result is the same for any number of dimensions). This data could be anything - for example, number of auto accidents vs miles driven, cost of soy vs annual rainfall, or even motion of planets vs time (as was the original application of linear regression) - anything in which you hope to find some trend in the data.

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