Results 31 to 40 of about 4,923 (258)

Bayesian spatial monotonic multiple regression [PDF]

Biometrika, 2018
We consider monotonic, multiple regression for a set of contiguous regions (lattice data). The regression functions permissibly vary between regions and exhibit geographical structure. We develop new Bayesian non-parametric methodology which allows for both continuous and discontinuous functional shapes and which are estimated using marked point ...
Rohrbeck, Christian, Costain, Deborah Ann, Frigessi, Arnoldo   +2 more
openaire   +4 more sources

Multi-Physics Monotone Score Transport for Unsupervised Domain Adaptation of Continuous Tool Wear Prediction

Sensors
Cross-material continuous tool wear prediction is difficult because a model must preserve the physical wear scale, not only align high-dimensional sensor features.
Enhao Cui, Runshan Hu, Weina Zhang, Zihan Fei, Chenyang Zhu   +4 more
doaj   +1 more source

Bayesian Semiparametric Regression Analysis of Multivariate Panel Count Data

Stats, 2022
Panel count data often occur in a long-term recurrent event study, where the exact occurrence time of the recurrent events is unknown, but only the occurrence count between any two adjacent observation time points is recorded.
Chunling Wang, Xiaoyan Lin
doaj   +1 more source

Data‐Driven SuStaIn Model of Disability Progression in Amyotrophic Lateral Sclerosis

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To determine whether ordinal Subtype and Stage Inference (SuStaIn) applied to routine ALSFRS‐R item scores can identify reproducible disability progression patterns in amyotrophic lateral sclerosis (ALS) and provide clinically meaningful staging.
Giammarco Milella, Veria Vacchiano, Vittorio Velucci, Stefano Zoccolella, Rocco Liguori, Giovanni Defazio   +5 more
wiley   +1 more source

Adaptive Monotone Shrinkage for Regression

, 2015
We develop an adaptive monotone shrinkage estimator for regression models with the following characteristics: i) dense coefficients with small but important effects; ii) a priori ordering that indicates the probable predictive importance of the features.
Zhuang Ma, Dean P. Foster, Robert A. Stine   +2 more
openaire   +3 more sources

Multi-quantile systemic financial risk based on a monotone composite quantile regression neural network

Frontiers in Physics
This study proposes a novel perspective to calibrate the conditional value at risk (CoVaR) of countries based on the monotone composite quantile regression neural network (MCQRNN).
Chao Ren, Ziyan Zhu, Donghai Zhou
doaj   +1 more source

On estimation for accelerated failure time models with small or rare event survival data

BMC Medical Research Methodology, 2022
Background Separation or monotone likelihood may exist in fitting process of the accelerated failure time (AFT) model using maximum likelihood approach when sample size is small and/or rate of censoring is high (rare event) or there is at least one ...
Tasneem Fatima Alam, M. Shafiqur Rahman, Wasimul Bari   +2 more
doaj   +1 more source

Utility of the APE2 Score as a Diagnostic Tool for Autoimmune Encephalitis

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To retrospectively evaluate the diagnostic performance of the Antibody Prevalence in Epilepsy and Encephalopathy (APE2) score relative to clinician‐adjudicated autoimmune encephalitis (AE) and the Graus criteria in a tertiary neuroimmunology referral cohort, including antibody‐negative AE.
Bijoya Basu, Sophia F. Damman, Samhitha M. Rai, Hesham Abboud   +3 more
wiley   +1 more source

Characterization of Defect Distribution in an Additively Manufactured AlSi10Mg as a Function of Processing Parameters and Correlations with Extreme Value Statistics

Advanced Engineering Materials, EarlyView.
Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt, Varma Kvvssn, Hossein Laieghi, Zia Uddin, Peyman Ansari, E. Kıvanç Sadak, Can Barış Toprak, Hüseyin Kızıl, Enrico Salvati   +8 more
wiley   +1 more source

Enhanced Projection Method for the Solution of the System of Nonlinear Equations Under a More General Assumption than Pseudo-Monotonicity and Lipschitz Continuity

Mathematics
In this manuscript, we propose an efficient algorithm for solving a class of nonlinear operator equations. The algorithm is an improved version of previously established method. The algorithm’s features are as follows: (i) the search direction is bounded
Kanikar Muangchoo, Auwal Bala Abubakar
doaj   +1 more source