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Multiscale stochastic volatility for variance swaps with constant elasticity of variance
The variance swap is one of volatility derivatives popularly used for the risk management of financial instruments traded in volatile market. An...
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Variance Estimation in Spatially Balanced Sampling
In spatially balanced sampling designs, joint inclusion probabilities for neighborhood units are often zero, or near to zero, because the sampling...
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An Innovation Sequence Variance Interference Detection Algorithm Based on Reference Noise
Spoofing interference poses a threat to the positioning and timing security of GNSS that cannot be ignored. In traditional spoofing interference...
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Ranking-Based Band Selection Using Correlation and Variance Measure
Contiguous narrow bands of hyperspectral images greatly increase computational complexity. Redundancy reduction is therefore necessary. In this...
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Beyond expectations: residual dynamic mode decomposition and variance for stochastic dynamical systems
Koopman operators linearize nonlinear dynamical systems, making their spectral information of crucial interest. Numerous algorithms have been...
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Linear Combinations of Time Series Models with Minimal Forecast Variance
In this paper construction of optimal combination of time series forecasts (by quality of prediction or forecast variance evaluation) is considered....
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Variance Optimization Based on Guided Anchor Siamese Network for Target-of-interest Object Recognition in Autonomous Mobile Robots
Deep learning models are used to track target-of-interest (ToI) objects with autonomous mobile robots (AMRs). A Siamese network based on few-shot...
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Non-parametric Nearest Neighbor Classification Based on Global Variance Difference
As technology improves, how to extract information from vast datasets is becoming more urgent. As is well known, k-nearest neighbor classifiers are...
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Uncertain random portfolio optimization via semi-variance
Semi-variance is a similar measure to variance, but it only considers values that are below the expected value. As important roles of semi-variance...
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Adaptive Estimation of Measurement Noise Variance in Kinematic Precise Point Positioning
The performance of the kinematic Precise Point Positioning (PPP) depends on accurate measurement noise covariance matrix. In this paper, an...
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A Mixed-Mode Decomposition Denoising Algorithm Based on Variance Estimation
Conventional denoising algorithms have poor effect when dealing with nonlinear or non-stationary signals, and it is also difficult to select...
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A new reliability method combining adaptive Kriging and active variance reduction using multiple importance sampling
This article describes a new adaptive Kriging method combined with adaptive importance sampling approximating the optimal auxiliary by iteratively...
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Stochastic efficient global optimization with high noise variance and mixed design variables
Engineering design and optimization commonly require the minimization of expected value functions with high noise variance and mixed/discrete design...
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Comparison of Classic Mean-Variance and Fuzzy Model Approaches to Portfolio Selection Problem
Selection of an efficient portfolio is a sophisticated process assuming decision making on proper distribution of funds based on possible expected...
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Ill-Posedness and the Bias-Variance Tradeoff in Residual Stress Measurement Inverse Solutions
BackgroundRelaxation methods determine residual stresses by measuring the deformations produced by incremental removal of a subdomain of the...
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Co-variance Based Adaptive Threshold Spectrum Detection Optimized with Chameleon Swarm Optimization for Optimum Threshold Selection in Cognitive Radio Networks
In cognitive radio networks, Spectrum sensing is most important task for avoiding the unacceptable interference to primary users. The performance of...
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Heuristic Methods Solving Markowitz Mean-Variance Portfolio Optimization Problem
In this paper, we introduce two heuristic methods for solving Markowitz mean-variance portfolio optimization problem with cardinality constraints and...
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Use of calibration constraints and linear moments for variance estimation under stratified adaptive cluster sampling
Analyzing sample data is a difficult task made more difficult whenever the data contains extreme values that impair the precision of variance...
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A Multisource PNT Fusion Algorithm Based on a Variance Genetic Model
As one of the long-term challenges faced by the International Maritime Organization (IMO), the global navigation satellite system (GNSS) has become...
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Adaptive Observation Noise Variance Algorithm Based on Innovation Repair
When the observation value is abnormal, the traditional robust estimation method only reduces the weight of the abnormal observation value, but does...