Using random effects models in prediction problems
The Unofficial Google Data Science Blog
MARCH 31, 2016
Random Effect Models We will start by describing a Gaussian regression model with known residual variance $sigma_j^2$ of the $j$th training record's response, $y_j$. Often our data can be stored or visualized as a table like the one shown below. Applied Stochastic Models in Business and Industry, 26 (2010): 639-658. [10]
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