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.

Partial linear models have been widely used as flexible method for modelling linear components in conjunction with non-parametric ones. Despite the presence of the non-parametric part, the linear, ...

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

Journal of the Royal Statistical Society. Series B (Statistical Methodology), Vol. 78, No. 5 (NOVEMBER 2016), pp. 1079-1102 (24 pages) We consider testing regression coefficients in high dimensional ...