This writer used homebrew econometrics to advocate for a housing proposal in Pentagon City. Others with data analysis acumen can do this, too.

Researchers have developed an uncertainty quantification-based framework for predicting degradation trends in proton exchange ...

The tropical dry deciduous forests of west central India are vital ecosystems that support local communities and play a significant role in mitigating climate change. However, their full contribution ...

Abstract: Kernel density estimation (KDE), a flexible nonparametric technique unconstrained by specific data distribution assumptions, is extensively employed in fault modeling. However, its ...

Reconstructing the diverse conformations of biomolecules from cryoelectron microscopy datasets remains a longstanding challenge. Here, we present a method that surpasses current approaches across ...

This special report introduces small area estimation (SAE) as a modern approach for producing reliable, stand-level forest inventory information Small area estimation (SAE) is a set of statistical ...

Nonparametric methods provide a flexible framework for estimating the probability density function of random variables without imposing a strict parametric model. By relying directly on observed data, ...

This study introduces two-dimensional (2D) Kernel Density Estimation (KDE) plots as a novel tool for visualising Training Intensity Distribution (TID) in biathlon. The goal was to assess how KDE plots ...

This repository implements a method to estimate a density-ratio. It is largely based on https://github.com/ermongroup/dre-infinity/. We have cleaned up the code a bit ...

Abstract: The accurate and rapid spectral redshift estimation is always the bottleneck that restricts the in-orbit service of the spectral redshift navigation system (SRNS) for deep space navigation.