Abstract: The energy consumption caused by battery thermal management of electric vehicles can be reduced using predictive control. A predictive controller needs a prediction model of the battery ...

Katharine Beer is a writer, editor, and archivist based in New York. She has a broad range of experience in research and writing, having covered subjects as diverse as the history of New York City's ...

This example illustrates the use of the new class QuantileConfidence based on data and has IMO some room for improvement: The sample is defined through a long cell with one point per row, which is not ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of neural network quantile regression. The goal of a quantile regression problem is to predict a single numeric ...

The L1 norm (when q=0.5) tends to allow the fit to be better at more points at the expense of allowing some points to fit worse, as the plot of the residuals against the least squares residuals: ...

Background The effectiveness of tax increases in reducing tobacco consumption relies on the tobacco retailers and producers passing on increases to consumers (tax pass-through). Previous UK research ...

Frequently Asked Question (FAQ) pages (or informational hubs) enable your business to respond, react, and anticipate the needs of your audience more quickly and appropriately than other types of ...

During the COVID-19 pandemic, daily infections exhibited different pattern. It multiplied at an exponential rate, in the beginning. Due to physical restrictions imposed during the lockdown, this ...

The chart called "Average Cumulative Returns by Quantile" in examples - Event Study has y-axis values of Mean Return (bps) in range 296000-304000! It seems to me, it is too high to be realistic! Or ...

This paper discusses the asymmetric effect of air quality (AQ) on stock returns (SR) in China's health industry through the quantile-on-quantile (QQ) regression method. Compared to prior literature, ...

Abstract: In this paper, we propose a continuous-time distributed algorithm for the dynamic quantile problem. The problem is to find the quantile of time-varying signals in a network of agents, each ...