Results 111 to 120 of about 26,219 (311)
, 2011 Copyright [2011] IEEE. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Brunel University's products or services.
Zeng, N +9 more
core +1 more source
Forecasting With Dynamic Factor Models Estimated by Partial Least Squares
Journal of Forecasting, EarlyView.ABSTRACT Dynamic factor models (DFMs) have found great success in nowcasting and short‐term macroeconomic forecasting when incorporating large sets of predictive information. The factor loadings are typically estimated cross‐sectionally with principal component analysis (PCA) or maximum likelihood (ML), which ignore whether the factors have predictive ...
Samuel Rauhala
wiley +1 more source
ActuatorsIn the actual working environment, most equipment models present nonlinear characteristics. For nonlinear system filtering, filtering methods such as the Extended Kalman Filter (EKF), Unscented Kalman Filter (UKF), and Cubature Kalman Filter (CKF) have ...
Chengyi Li, Chenglin Wen
doaj +1 more source
Kalman filtering and smoothing for linear wave equations with model error [PDF]
, 2011 Filtering is a widely used methodology for the incorporation of observed data into time-evolving systems. It provides an online approach to state estimation inverse problems when data are acquired sequentially.
A M Stuart +6 more
core +1 more source
Nowcasting World Trade With Machine Learning: A Three‐Step Approach
Journal of Forecasting, EarlyView.ABSTRACT We nowcast world trade using machine learning, distinguishing between tree‐based methods (random forest and gradient boosting) and their linear‐regression‐based counterparts (macroeconomic random forest and gradient boosting—linear). While much less used in the literature, the latter are found to outperform not only the tree‐based techniques ...
Menzie Chinn +2 more
wiley +1 more source
An Improved Kalman Filtering Method for Indoor Location
, 2016 Indoor real time location technology is widely used in large indoor space, and the location algorithm is the key part of the technology. For the signal interference problems in non-line of sight (NLOS) environment and the deficiency of the existing ...
Guo TT(郭廷廷) +5 more
core +1 more source
Discrete Dynamics in Nature and Society, 2015 This paper is concerned with the optimal Kalman filtering problem for a class of discrete stochastic systems with multiplicative noises and random two-step sensor delays.
Dongyan Chen +3 more
doaj +1 more source
Robust adaptive estimators for nonlinear systems
, 2013 This paper is concerned with the development of new adaptive nonlinear estimators which incorporate adaptive estimation techniques for system noise statistics with the robust technique.
R. Katebi +3 more
core +1 more source
Time‐Varying Skewness–Kurtosis Dynamics in Bitcoin Markets
Journal of Futures Markets, EarlyView.ABSTRACT This paper examines the relationship between skewness and kurtosis in Bitcoin spot and futures markets using high‐frequency data. We document a strong convex skewness–kurtosis relationship consistent with theoretical moment restrictions. Trading activity is positively associated with realized kurtosis, particularly in futures markets, though ...
Ariston Karagiorgis, Antonis Ballis
wiley +1 more source
Application of the Extended Kalman filter to fuzzy modeling: Algorithms and practical implementation
, 2011 Modeling phase is fundamental both in the analysis process of a dynamic system and the design of a control system. If this phase is in-line is even more critical and the only information of the system comes from input/output data.
Jose Manuel Andujar Marquez +11 more
core +1 more source