Results 111 to 120 of about 212,322 (298)
On the Stability of Bayes Estimators for Gaussian Processes. [PDF]
The Annals of Statistics, 1982 Consider a Gaussian signal process \(X=(X_ t)\) observed in the presence of an additive Gaussian noise process \(N=(N_ t)\) for t in [0,T]. The paper is concerned with the behaviour of the Bayes estimator \(\delta_ 0\) under departures from Gaussian law by the prior or noise processes. The problem of choosing a suitable contamination model is discussed.
openaire +2 more sources
On the performance of small-area estimators: Fixed vs. random area parameters [PDF]
Most methods for small-area estimation are based on composite estimators derived from design- or model-based methods. A composite estimator is a linear combination of a direct and an indirect estimator with weights that usually depend on unknown ...
Alex Costa, Eva Ventura, Albert Satorra
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Muscle Control of an Extra Robotic Digit
Advanced Robotics Research, EarlyView.This study compares muscle‐ and movement‐based control for operating a supernumerary robotic thumb. While movement control performs better in the proposed tasks, muscle‐based (EMG) control promotes broader motor learning. The results highlight the promise and challenges of using biosignals for human augmentation, offering new insights into intuitive ...
Julien Russ +7 more
wiley +1 more source
"Prediction in Multivariate Mixed Linear Models" [PDF]
The multivariate mixed linear model or multivariate components of variance model with equal replications is considered.The paper addresses the problem of predicting the sum of the regression mean and the random e ects.When the feasible best linear ...
Tatsuka Kubokawa, M. S. Srivastava
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Advanced Robotics Research, EarlyView.This review maps the methods to monitor robots’ health by fusing vibration, sound, control signals, vision, force, and oil information with artificial intelligence. It identifies deep learning, transfer learning, digital twins, and physics‐informed models as key methodological pathways enabling earlier diagnosis, safer human–robot collaboration, and ...
Yuting Qiao +6 more
wiley +1 more source
AN EMPIRICAL BAYES APPROACH TO MODELING DROUGHT [PDF]
This paper illustrates an alternative approach to estimating the occurrence of drought. The empirical Bayes methodology was developed because of deficiencies in time-series and regression analysis with respect to prediction of drought. This manuscript is
Chamberlain, P.J.
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Identifiability of differentiable bayes estimators of the uniform scale parameter [PDF]
, 2000 The problem of estimating the uniform scale parameter under the squared error loss function is investigated from a Bayesian viewpoint. A complete characterization of differentiable Bayes estimators and generalized Bayes estimators is given.
Lillo Rodríguez, Rosa Elvira
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Learning‐Based Soft Robotic Grasping: Recent Progress and Remaining Challenges
Advanced Robotics Research, EarlyView.This review analyzes learning‐based soft robotic grasping from a pipeline‐oriented perspective, encompassing soft gripper design, multimodal sensing, and learning‐based planning and control. It surveys key neural network architectures and benchmark datasets and identifies critical challenges such as sim‐to‐real transfer, generalization, and continual ...
Arnab Majumder +3 more
wiley +1 more source
Bayes and pseudo-Bayes estimates of conditional probabilities and their reliability [PDF]
, 1993 Various ways of estimating probabilities, mainly within the Bayesian framework, are discussed. Their relevance and application to machine learning is given, and their relative performance empirically evaluated. A method of accounting for noisy data is given and also applied.
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Policy-related small.area estimation [PDF]
A method of small-area estimation with a utility function is developed. The utility characterises a policy planned to be implemented in each area, based on the area?s estimate of a key quantity.
LONGFORD Nicholas Tibor
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