We investigate the extension of the nonparametric regression technique of local polynomial fitting with a kernel weight to generalized linear models and quasi-likelihood contexts. In the ordinary ...

At its core, the SPARKLINE function in Google Sheets takes a row of numbers and turns them into a mini chart that lives right inside a single cell. Instead of inserting a full-sized chart that eats up ...

Abstract: This paper presents stability analysis of polynomial fuzzy-model-based (FMB) control systems using the sum-of-squares (SOS) approach. Recently, stability analysis of the polynomial ...

Abstract: This article addresses the problem of finite-time asynchronous switching control for fuzzy Markov jump systems (FMJSs) using polynomial membership functions. Firstly, a Lyapunov-Krasovskii ...

Adam Hayes, Ph.D., CFA, is a financial writer with 15+ years Wall Street experience as a derivatives trader. Besides his extensive derivative trading expertise, Adam is an expert in economics and ...

This section focuses on the key features and methods for working with linear graphs. It demonstrates how to sketch graphs from rules, derive rules from graphs, and calculate key features such as the ...

Struct2GO is a protein function prediction model based on self-attention graph pooling, which utilizes structural information from AlphaFold2 to augment the accuracy and generality of the model's ...

The rapid accumulation of protein sequence data, coupled with the slow pace of experimental annotations, creates a critical need for computational methods to predict protein functions. Existing models ...

Dr Bahman Kalantari discusses a piece of software that he has developed through his research into polynomial root-finding. With this software, users can explore the world of polynomials and their ...

One powerful way to do this is through a routine called slow reveal graphs.

Comparing a map of the neurons in a nematode worm - the connectome - with a map of how signals travel across those neurons ...