Writers' rooms: theories of contemporary authorship in portraits of creative spaces

This article analyzes two series of photographs and essays on writers’ rooms published in England and Canada in 2007 and 2008. The Guardian’s Writers Rooms series, with photographs by Eamon McCabe, ran in 2007. In the summer of 2008, The Vancouver International Writers and Readers Festival began to post its own version of The Guardian column on its website by displaying, each week leading up to the Festival in September, a different writer’s “writing space” and an accompanying paragraph. I argue that these images of writers’ rooms, which suggest a cultural fascination with authors’ private compositional practices and materials, reveal a great deal about theoretical constructions of authorship implicit in contemporary literary culture. Far from possessing the museum quality of dead authors’ spaces, rooms that are still being used, incorporating new forms of writing technology, and having drafts of manuscripts scattered around them, can offer insight into such well-worn and ineffable areas of speculation as inspiration, singular authorial genius, and literary productivity.

Probabilistic wind power forecasts with an inverse power curve transformation and censored regression

Forecasting wind power is an important part of a successful integration of wind power into the power grid. Forecasts with lead times longer than 6 h are generally made by using statistical methods to post-process forecasts from numerical weather prediction systems. Two major problems that complicate this approach are the non-linear relationship between wind speed and power production and the limited range of power production between zero and nominal power of the turbine. In practice, these problems are often tackled by using non-linear non-parametric regression models. However, such an approach ignores valuable and readily available information: the power curve of the turbine's manufacturer. Much of the non-linearity can be directly accounted for by transforming the observed power production into wind speed via the inverse power curve so that simpler linear regression models can be used. Furthermore, the fact that the transformed power production has a limited range can be taken care of by employing censored regression models. In this study, we evaluate quantile forecasts from a range of methods: (i) using parametric and non-parametric models, (ii) with and without the proposed inverse power curve transformation and (iii) with and without censoring. The results show that with our inverse (power-to-wind) transformation, simpler linear regression models with censoring perform equally or better than non-linear models with or without the frequently used wind-to-power transformation.