Results 91 to 100 of about 4,458,250 (263)

Improving Radio Source Count Estimation Using Kernel Density Estimation

The Astrophysical Journal
Radio source counts provide a fundamental census of cosmic radio emission, yet their estimation is usually based on coarse histograms that suffer from bin-choice bias, boundary effects, and survey incompleteness.
Luozhenhan Liu, Zunli Yuan, Wenjie Wang, Chuanqi Li   +3 more
doaj   +1 more source

Defect‐Templated Phase Engineering in Atomically Thin Metals

Advanced Materials, EarlyView.
Graphene defects are transformed from passive imperfections into programmable templates for phase‐selective growth of atomically thin silver. Plasma‐generated boundary defects favor Ag(1), whereas sp3‐rich zero‐layer graphene promotes Ag(2). This defect‐directed intercalation links local graphene chemistry to crystalline phase, electronic structure ...
Arpit Jain, Boyang Zheng, Sawani Datta, Kanchan Ulman, Jakob Henz, Matthew Wei‐Jun Liu, Van Dong Pham, Wen He, Chengye Dong, Li‐Syuan Lu, Alexander Vera, Nader Sawtarie, Wesley Auker, Ke Wang, Bob Hengstebeck, Zachary W. Henshaw, Shreya Mathela, Maxwell Wetherington, William H. Blades, Kenneth Knappenberger, Ursula Wurstbauer, Su Ying Quek, Ulrich Starke, Shengxi Huang, Vincent H. Crespi, Joshua A. Robinson   +25 more
wiley   +1 more source

sparr: Analyzing Spatial Relative Risk Using Fixed and Adaptive Kernel Density Estimation in R [PDF]

The estimation of kernel-smoothed relative risk functions is a useful approach to examining the spatial variation of disease risk. Though there exist several options for performing kernel density estimation in statistical software packages, there have ...
Tilman M. Davies, Jonathan. C Marshall, Martin L. Hazelton   +2 more
core  

2D Abrupt Nano‐Junctions Blending sp–sp2 Bonds on Atomically Precise Heterostructures

Advanced Materials, EarlyView.
A lateral heterostructure between atomically precise sp–sp2$^2$ metalated graphdiyne and sp2$^2$ graphene nanoribbons is realized by on‐surface synthesis and investigated by STM and DFT. The impact of on‐surface synthesis byproducts on covalent junction formation yield is unveiled.
Alice Cartoceti, Simona Achilli, Masoumeh Alihosseini, Adriana E. Candia, Enrico Beltrami, Paolo D'Agosta, Alessio Orbelli Biroli, Francesco Sedona, Andrea Li Bassi, Jorge Lobo‐Checa, Carlo S. Casari   +10 more
wiley   +1 more source

Transformation kernel density estimation of actuarial loss functions [PDF]

A transformation kernel density estimator that is suitable for heavy-tailed distributions is discussed. Using a truncated Beta transformation, the choice of the bandwidth parameter becomes straightforward.
Montserrat Guillen (Universitat de Barcelona), Jens Perch Nielsen (City University London), Catalina Bolance (Universitat de Barcelona)   +2 more
core  

Descriptors to Dynamics: A Materials and Device Perspective on in‐Materio Physical Reservoir Computing for Neuromorphic Edge Intelligence

Advanced Materials, EarlyView.
Intrinsic material dynamics are harnessed as computational resources for neuromorphic in‐materio physical reservoir computing. Defects, ionic motion, interfaces, percolation, geometry, and biasing shape transient states that provide fading memory, nonlinearity, and high‐dimensional projection for simple readout. A descriptor‐to‐dynamics framework links
Kshitij RB Singh, Alif Syafiq Kamarol Zaman, Muzhen Xu, Yuki Usami, Saptarshi Das, Hirofumi Tanaka   +5 more
wiley   +1 more source

A Bayesian approach to bandwidth selection for multivariate kernel regression with an application to state-price density estimation. [PDF]

Multivariate kernel regression is an important tool for investigating the relationship between a response and a set of explanatory variables. It is generally accepted that the performance of a kernel regression estimator largely depends on the choice of ...
Robert D. Brooks, Maxwell L. King, Xibin Zhang   +2 more
core  

Distributional CNN-LSTM, KDE, and Copula Approaches for Multimodal Multivariate Data: Assessing Conditional Treatment Effects

Analytics
We introduce a distributional CNN-LSTM framework for probabilistic multivariate modeling and heterogeneous treatment effect (HTE) estimation. The model jointly captures complex dependencies among multiple outcomes and enables precise estimation of ...
Jong-Min Kim
doaj   +1 more source

Mapping Correlated Environmental Landscapes in the Fluorescence Response of a Pyrenylated Charge‐Transfer Probe via Data‐Driven Nonlinear Regression

Advanced Materials Interfaces, EarlyView.
A pyrenylated donor–acceptor probe exhibits environment‐dependent fluorescence governed by intramolecular charge transfer, restricted molecular motion, and supramolecular organization. Nonlinear regression accurately reconstructs fluorescence responses to viscosity, temperature, concentration, and pH, while correlated parameter maps reveal hidden ...
Harshal V. Barkale, Anakhi Hazarika, Nilanjan Dey   +2 more
wiley   +1 more source

Canonical Higher-Order Kernels for Density Derivative Estimation [PDF]

In this note we present r th order kernel density derivative estimators using canonical higher-order kernels. These canonical rescalings uncouple the choice of kernel and scale factor. This approach is useful for selection of the order of the kernel in a
Christopher F. Parmeter, Daniel J. Henderson   +1 more
core