Wavelets for Nonparametric Stochastic Regression with Pairwise Negative Quadrant Dependent Random Variables
Source abstract
Abstract
We propose a wavelet based stochastic regression function estimator for the estimation of the regression function for a sequence of pairwise negative quadrant dependent random variables with a common one-dimensional probability density function. Some asymptotic properties of the proposed estimator are investigated. It is found that the estimators have similar properties to their counterparts studied earlier in literature.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Financial Risk and Volatility Modeling · Image and Signal Denoising Methods · Fuzzy Systems and Optimization
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