Results 71 to 80 of about 2,865,465 (299)

Fractional trends in unobserved components models

open access: yes, 2020
We develop a generalization of unobserved components models that allows for a wide range of long-run dynamics by modelling the permanent component as a fractionally integrated process. The model does not require stationarity and can be cast in state space form. In a multivariate setup, fractional trends may yield a cointegrated system.
Hartl, Tobias   +2 more
openaire   +2 more sources

Mapping Correlated Environmental Landscapes in the Fluorescence Response of a Pyrenylated Charge‐Transfer Probe via Data‐Driven Nonlinear Regression

open access: yesAdvanced Materials Interfaces, EarlyView.
A pyrenylated donor–acceptor probe exhibits environment‐dependent fluorescence governed by intramolecular charge transfer, restricted molecular motion, and supramolecular organization. Nonlinear regression accurately reconstructs fluorescence responses to viscosity, temperature, concentration, and pH, while correlated parameter maps reveal hidden ...
Harshal V. Barkale   +2 more
wiley   +1 more source

Revisiting the Dollar-Euro Permanent Equilibrium Exchange Rate: Evidence from Multivariate Unobserved Components Models [PDF]

open access: yes
We propose an alterative approach to obtaining a permanent equilibrium exchange rate (PEER), based on an unobserved components (UC) model. This approach offers a number of advantages over the conventional cointegration-based PEER. Firstly, we do not rely
Ronald MacDonald, Xiaoshan Chen
core  

magi: A Package for Inference of Dynamic Systems from Noisy and Sparse Data via Manifold-Constrained Gaussian Processes

open access: yesJournal of Statistical Software
This article presents the magi software package for the inference of dynamic systems. The focus of magi is on dynamics modeled by nonlinear ordinary differential equations with unknown parameters.
Samuel W. K. Wong   +2 more
doaj   +1 more source

Recent Advances of Slip Sensors for Smart Robotics

open access: yesAdvanced Materials Technologies, EarlyView.
This review summarizes recent progress in robotic slip sensors across mechanical, electrical, thermal, optical, magnetic, and acoustic mechanisms, offering a comprehensive reference for the selection of slip sensors in robotic applications. In addition, current challenges and emerging trends are identified to advance the development of robust, adaptive,
Xingyu Zhang   +8 more
wiley   +1 more source

Fitting State Space Models with EViews

open access: yesJournal of Statistical Software, 2011
This paper demonstrates how state space models can be fitted in EViews. We first briefly introduce EViews as an econometric software package. Next we fit a local level model to the Nile data.
Filip A. M. Van den Bossche
doaj  

Toward Perception‐Native Electronic Skin: Bio‐Inspired In‐/Near‐Sensor and Neuromorphic Computing for Humanoid Robots

open access: yesAdvanced Materials Technologies, EarlyView.
Dense tactile streams from across the humanoid body converge on collide in a central wiring and data bottleneck. By relocating computation closer to and then into the skin itself, near‐ and in‐sensor architectures, together with neuromorphic computing, chart a path toward perception‐native electronic skin, in which the conversion of stimulus into ...
Mijin Kim   +6 more
wiley   +1 more source

A Likelihood Ratio Test of Stationarity Based on a Correlated Unobserved Components Model [PDF]

open access: yes
We propose a likelihood ratio (LR) test of stationarity based on a widely-used correlated unobserved components model. We verify the asymptotic distribution and consistency of the LR test, while a bootstrap version of the test is at least first-order ...
Tara M. Sinclair   +2 more
core  

The STAMP Software for State Space Models

open access: yesJournal of Statistical Software, 2011
This paper reviews the use of STAMP (Structural Time Series Analyser, Modeler and Predictor) for modeling time series data using state-space methods with unobserved components.
Roy Mendelssohn
doaj  

Grounding Large Language Models for Robot Task Planning Using Closed‐Loop State Feedback

open access: yesAdvanced Robotics Research, EarlyView.
BrainBody‐Large Language Model (LLM) introduces a hierarchical, feedback‐driven planning framework where two LLMs coordinate high‐level reasoning and low‐level control for robotic tasks. By grounding decisions in real‐time state feedback, it reduces hallucinations and improves task reliability.
Vineet Bhat   +4 more
wiley   +1 more source

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