Nature

Nonparametric Methods in Probability Density Estimation

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, ...
Simon Fraser University

Density Estimation

Refer to Silverman (1986) or Scott (1992) for an introduction to nonparametric density estimation. PROC MODECLUS uses (hyper)spherical uniform kernels of fixed or variable radius. The density estimate ...
Open Access Government

Leveraging machine learning and robust small area estimation methods for stand-level forest inventory

This special report introduces small area estimation as a modern approach for producing reliable, stand-level forest ...
JSTOR Daily

Use of fecal DNA to estimate black bear density in an urban-wildland interface

Vol. 46, No. 4, Climate Adaptation Actions Machine Learning for Camera Traps Crippling Loss in Waterfowl (September 2022), pp. 1-14 (14 pages) American black bears (Ursus americanus) commonly ...
Simon Fraser University

Estimation Methods

A brief description of the methods used by the SYSLIN procedure follows. For more information on these methods, see the references at the end of this chapter. There are two fundamental methods of ...
ascopubs.org

Volumetric Breast Density Estimation From Three-Dimensional Reconstructed Digital Breast Tomosynthesis Images Using Deep Learning

We retrospectively analyzed 1,080 nonactionable three-dimensional (3D) reconstructed DBT screening examinations acquired between 2011 and 2016. Reference tissue segmentations were generated using ...