Results 61 to 70 of about 607,794 (304)

Robust nonparametric inference for the median

The Annals of Statistics, 2004
We consider the problem of constructing robust nonparametric confidence intervals and tests of hypothesis for the median when the data distribution is unknown and the data may contain a small fraction of contamination. We propose a modification of the sign test (and its associated confidence interval) which attains the nominal significance level ...
Yohai, V.J., Zamar, R.H.
openaire   +5 more sources

Multimodal Engagement Assessment in Children During Invented Story Paradigm With a Social Robot

Advanced Robotics Research, EarlyView.
A multimodal framework is proposed to assess children's engagement during storytelling interactions with a social robot. Gaze, physiological, and behavioral data are combined and validated against observer ratings. An automated gaze‐labeling strategy is introduced, and supervised classifiers achieve high accuracy. The study supports scalable engagement
Laura Fiorini, Elena Adelucci, Stefano Scatigna, Lorenzo Pugi, Alice Bruni, Benedetta Carotenuto, Chiara Pecini, Filippo Cavallo   +7 more
wiley   +1 more source

Robustness of nonparametric predictive inference for future order statistics [PDF]

, 2019
This paper considers robustness of Nonparametric Predictive Inference (NPI), in particular considering inference involving future order statistics. The concept of robust inference is usually aimed at development of inference methods which are not too ...
Alqifari, H.N., Coolen, F.P.A.
core   +1 more source

Time History Gaussian Process Regression for Modeling the Dynamics of Ankle Exoskeleton User Comfort

Advanced Robotics Research, EarlyView.
Exoskeletons need to be comfortable, but the perception of comfort may change over time. This study investigated if short‐term time history directly influences comfort. No previous trials’ input features were predictive of comfort. Including the previous trial's comfort score marginally improved model accuracy compared to a model using only the current
Axl Maberry, Bo Cheng, Anne E. Martin
wiley   +1 more source

Nonparametric estimation of conditional incremental effects

Journal of Causal Inference
Conditional effect estimation has great scientific and policy importance because interventions may impact subjects differently depending on their characteristics.
McClean Alec, Branson Zach, Kennedy Edward H.   +2 more
doaj   +1 more source

Robustness versus efficiency for nonparametric correlation measures. [PDF]

Nonparametric correlation measures at the Kendall and Spearman correlation are widely used in the behavioral sciences. These measures are often said to be robust, in the sense of being resistant to outlying observations.
Croux, Christophe, Dehon, Catherine
core  

Robustness

, 2022
This report summarizes how to systematically analyze a software architecture with respect to a quality attribute requirement for robustness. The report introduces the quality attribute of robustness and common forms of robustness requirements for ...
Philip Bianco (3891784), James Ivers (3887017), Sebastian Echeverria Galvez (5443520), Frederick Kazman (3892735)   +3 more
core   +1 more source

Mr BMT Achieves Systemic Macrophage Replacement With Preservation of Tissue Homeostasis

Advanced Science, EarlyView.
Microglia replacement by bone marrow transplantation (Mr BMT) enables systemic replacement of tissue‐resident macrophages. Despite persistent macrophage and tissue remodeling across multiple organs, core biological functions and innate immune responses remain preserved, supporting long‐term maintenance of organismal homeostasis and the therapeutic ...
Yufei Xu, Miaozhan Zou, Yunshang Bai, Yang He, Zhihao Jin, Baozhi Yang, Jinjin Du, Pei Ouyang, Yuanyuan Cai, Yuheng Zhang, Bingying Du, Chengcheng Ge, Jian‐an Gong, Xiaoyu Li, Yuanyi Zheng, Jing Ding, Bo Peng, Yanxia Rao   +17 more
wiley   +1 more source

Wasserstein Distributionally Robust Nonparametric Regression

CoRR
Wasserstein distributionally robust optimization (WDRO) strengthens statistical learning under model uncertainty by minimizing the local worst-case risk within a prescribed ambiguity set. Although WDRO has been extensively studied in parametric settings, its theoretical properties in nonparametric frameworks remain underexplored.
Changyu Liu, Yuling Jiao, Junhui Wang, Jian Huang   +3 more
openaire   +3 more sources

A Bistochastic Nonparametric Estimator [PDF]

We explore the relevance of adopting a bistochastic nonparametric estimator. This estimator has two main implications. First, the estimator reduces variability according to the robust criterion of second-order stochastic (and Lorenz) dominance. This is a
Rafael Salas, Juan Gabriel Rodríguez
core