Complex Mean and Variance of Linear Regression Model for High-Noised Systems by Kriging
Tomasz Suslo
TL;DR
This paper derives a complex-valued least-squares estimator for bias-noise mean and variance in high-noise systems using Kriging, providing a new approach to modeling uncertainty in such environments.
Contribution
It introduces a novel complex-valued estimator for mean and variance in high-noise linear regression models using Kriging, enhancing modeling accuracy.
Findings
Derived the complex-valued least-squares estimator for bias-noise mean.
Derived the complex-valued least-squares estimator for bias-noise variance.
Demonstrated improved estimation in high-noise systems.
Abstract
The aim of the paper is to derive the complex-valued least-squares estimator for bias-noise mean and variance.
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Taxonomy
TopicsRegional Economic and Spatial Analysis · Remote Sensing and Land Use · Advanced Statistical Methods and Models