In this chapter, we propose a log-linear model for the biases observed when analyzing model communities data. Our model expands the recent work from McLaren, Willis and Callahan (MWC) [eLife, 8:e46923 ...

The large model could then implement a simple learning algorithm to train this smaller, linear model to complete a new task, using only information already contained within the larger model.

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of the linear support vector regression (linear SVR) technique, where the goal is to predict a single numeric ...

We consider marked empirical processes indexed by a randomly projected functional covariate to construct goodness-of-fit tests for the functional linear model with scalar response. The test statistics ...

In traditional models like linear regression and ANOVA, assumptions such as linearity, independence of errors, homoscedasticity, and normality of residuals are foundational.

Recent literature contains several expositions of the log-linear modeling (LLM) capability of analyzing multiway contingency tables. This method has been proposed as a way of overcoming the ...

In a thermally linear system, superposition may be applied to predict the transient response of the system to step changes in input power. This article is the second in a two-part series.