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Power prior elicitation in Bayesian quantile regression [PDF]

, 2011
This article has been made available through the Brunel Open Access Publishing Fund - Copyright @ 2011 Rahim Alhamzawi and Keming Yu.We address a quantile dependent prior for Bayesian quantile regression.
Rahim Alhamzawi, Yu, K, Keming Yu, Alhamzawi, R   +3 more
core   +1 more source

Memristive‐Gated RC‐Delay Synaptic Transistors for Time‐Encoded Analog in‐Memory Computing

Advanced Functional Materials, EarlyView.
A Memristive‐Gated Transistor for Time‐Encoded Analog In‐Memory Computing — By exploiting the RC delay of a self‐rectifying interface‐type memristor, nonlinear I–V distortion is structurally bypassed, enabling 3‐bit nonvolatile memory, spike‐timing‐based analog encoding, and hardware‐calibrated reservoir‐computing validation within a unified device ...
Yun‐Seo Shin, Eunjoo Yoo, Ki‐Hoon Son, Hyun‐Sik Kim, Dae‐Hee Han, Jeong Hyeon Son, Seung Hwan Lee, Hong‐Sub Lee   +7 more
wiley   +1 more source

ANALISIS PERTAMBAHAN TINGGI BADAN BALITA STUNTING DI PROVINSI SUMATERA BARAT MENGGUNAKAN METODE REGRESI KUANTIL BINER BAYESIAN

Jurnal Lebesgue
Stunting is one of the national health problems in Indonesia, where children experience growth failure. This study aims to construct a model for the classification of height gain of stunting toddlers in West Sumatra Province using the Bayesian binary ...
Cintya Mukti, Ferra Yanuar, Dodi Devianto   +2 more
doaj   +1 more source

Correction to: “Posterior Consistency of Bayesian Quantile Regression Based on the Misspecified Asymmetric Laplace Density”

Bayesian Analysis, 2017
In this note, we highlight and provide corrections to two errors in the paper: Karthik Sriram, R.V. Ramamoorthi, Pulak Ghosh (2013) “Posterior Consistency of Bayesian Quantile Regression Based on the Misspecified Asymmetric Laplace Density”, Bayesian Analysis, Vol 8, Num 2, pg 479–504.
Sriram, Karthik, Ramamoorthi, R.V.
openaire   +2 more sources

Microscale Mapping of Fiber Strain and Damage in Composite Wrinkled Laminates Using Computed Tomography Assisted Wide‐Angle X‐Ray Scattering

Advanced Science, EarlyView.
This study combines full‐field tomography with diffraction mapping to quantify radial (ε002$\varepsilon _{002}$) and axial (ε100$\varepsilon _{100}$) lattice strain in wrinkled carbon‐fiber specimens for the first time. Radial microstrain gradients (−14.5 µεMPa$\varepsilon \mathrm{MPa}$−1) are found to signal damage‐prone zones ahead of failure, which ...
Hoang Minh Luong, James Trevarthen, Igor Dolbnya, Wadwan Singhapong, Nicholas Pilato, Richard Butler, Jiraphant Srisuriyachot, Alexander J. G. Lunt   +7 more
wiley   +1 more source

A New Flexible Four Parameter Bathtub Curve Failure Rate Model, and Its Application to Right-Censored Data

IEEE Access, 2023
This article introduces a new flexible four parameter distribution by convolution of the exponential and Weibull distribution using the odd function transformation, which offers greater flexibility in terms of fit, its called the modified exponential ...
Laila A. Al-Essa, Mustapha Muhammad, M. H. Tahir, Badamasi Abba, Jinsen Xiao, Farrukh Jamal   +5 more
doaj   +1 more source

Physics‐Constrained Constitutive Learning of Rate‐Limiting Timescales for Efficient Hydrogen‐Based Direct Reduction for Green Steel Making

Advanced Science, EarlyView.
A conversion‐resolved constitutive framework is developed for the hydrogen‐based direct reduction of iron oxide pellets. Effective reaction and transport timescales are inferred directly from measured trajectories and mapped against operating conditions, pellet architecture, and composition. The analysis reveals how late‐stage transport control emerges
Anurag Bajpai, Barak Ratzker, Pasquale Cavaliere, Dierk Raabe   +3 more
wiley   +1 more source

Generative AI for Bayesian Computation

Entropy
Generative Bayesian Computation (GBC) provides a simulation-based approach to Bayesian inference. A Quantile Neural Network (QNN) is trained to map samples from a base distribution to the posterior distribution.
Nick Polson, Vadim Sokolov
doaj   +1 more source

Shaky Student Growth? A Comparison of Robust Bayesian Learning Progress Estimation Methods

Journal of Intelligence, 2022
Monitoring the progress of student learning is an important part of teachers’ data-based decision making. One such tool that can equip teachers with information about students’ learning progress throughout the school year and thus facilitate monitoring ...
Boris Forthmann, Natalie Förster, Elmar Souvignier   +2 more
doaj   +1 more source

Quantile-Quantile plot of RT data points of the total 6000 observations showing normality in distribution.

, 2023
Quantile-Quantile plot of RT data points of the total 6000 observations showing normality in distribution.
Kiran Kishore (16747959), Pranesh Bhargava (3388448), Krithika Nambiar (16747956)   +2 more
core   +1 more source