Results 141 to 150 of about 607,854 (297)
INTRODUCING MODEL UNCERTAINTY IN TIME SERIES BOOTSTRAP [PDF]
It is common in parametric bootstrap to select the model from the data, and then treat it as it were the true model. Kilian (1998) have shown that ignoring the model uncertainty may seriously undermine the coverage accuracy of bootstrap confidence ...
Andrés M. Alonso +2 more
core
Advanced Science, EarlyView.The IgLec gene family generates both protein‐coding antiviral effectors and non‐coding transcripts. Upon viral infection, non‐coding transcripts are preferentially targeted by viral miR‐N48, thereby buffering protein‐coding isoforms from repression. Depletion of these decoy transcripts compromises antiviral defense, revealing a non‐coding RNA‐mediated ...
Ying Huang +5 more
wiley +1 more source
A Score Based Approach to Wild Bootstrap Inference [PDF]
We propose a generalization of the wild bootstrap of Wu (1986) and Liu (1988) based upon perturbing the scores of M-estimators. This "score bootstrap" procedure avoids recomputing the estimator in each bootstrap iteration, making it substantially less ...
Andres Santos, Patrick M. Kline
core
Gut Microbial Topology and Metabolic Signatures Associated With Colorectal Neoplasia
Advanced Science, EarlyView.The gut microbiota organizes into two robust association patterns linked to colorectal neoplasia risk. Topological shifts in microbial networks are associated with metabolite alterations and may shape host responses during disease development. ABSTRACT Alterations of gut microbial communities impact health.
Kai Song +13 more
wiley +1 more source
Bootstrap Confidence Sets for the Number of Components in Finite Mixture Regression Models
MathematicsFinite mixture regression analyses usually treat the selected number of components as fixed, although neighboring orders may be difficult to distinguish. This paper develops a set-valued procedure for the order of a Gaussian finite mixture regression.
Mohieddine Rahmouni
doaj +1 more source
Statistical Analysis of Random Simulations: Bootstrap Tutorial [PDF]
The bootstrap is a simple but versatile technique for the statistical analysis of random simulations.This tutorial explains the basics of that technique, and applies it to the well-known M/M/1 queuing simulation.In that numerical example, different ...
Deflandre, D., Kleijnen, J.P.C.
core
PrOMet: Accurate and Robust Metal‐Binding Site and Type Prediction
Advanced Science, EarlyView.PrOMet is a two‐stage deep learning framework for jointly predicting metal‐binding sites and ion identities from protein structures. Surface candidate sites are first pruned, followed by refinement of the most probable sites and metal types. This hierarchical strategy enables robust and accurate metal prediction for cryo‐EM and AlphaFold‐derived ...
Gangeun Park, Chaok Seok, Hahnbeom Park
wiley +1 more source
Advanced Science, EarlyView.DAIMS is a multimodal model for treatment stratified risk and survival assessment in colorectal cancer. Training draws on pathology, genomics, and clinical reports, yet inference requires only whole slide images, and adaptation to new cohorts proceeds without target survival outcomes.
Chuangjie Cao +15 more
wiley +1 more source
Advanced Science, EarlyView.An advanced, long‐term human skin platform maintains native skin structure and key tissue functions for up to four weeks. The platform models chronic inflammation, aging‐related skin changes, and UVB damage, enabling drug and topical interventions—including anti‐inflammatory therapy, senolytic treatment, and sunscreen—to be evaluated in intact human ...
Purnendu Kumar Sharma +14 more
wiley +1 more source
Groupcompare: A holistic approach to two sample data analysis
SoftwareXThe groupcompare R package provides a unified framework for two-sample statistical comparisons. It addresses critical limitations of traditional methods by integrating parametric, non-parametric, permutation, and bootstrap-based techniques within a ...
Zeynel Cebeci +3 more
doaj +1 more source