arXiv 6 Aug 2019 · Statistics — Methodology · publishedIEEE Access (2019) · 1 citations (OpenAlex)
arXiv:1908.02166 · PDF · DOI · OpenAlex · Extracted main text
A new and an enriched JPEG algorithm is provided for identifying redundancies in a sequence of irregular noisy data points which also accommodates a reference-free criterion function. Our main contribution is by formulating analytically (instead of approximating) the inverse of the transpose of JPEGwavelet transform without involving matrices which are computationally cumbersome. The algorithm is suitable for the widely-spread situations where the original data distribution is unobservable such as in cases where there is deficient representation of the entire population in the training data (in machine learning) and thus the covariate shift assumption is violated. The proposed estimator corrects for both biases, the one generated by endogenous truncation and the one generated by endogenous covariates. Results from utilizing 2,000,000 different distribution functions verify the applicability and high accuracy of our procedure to cases in which the disturbances are neither jointly nor marginally normally distributed.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | J. J. Heckman, “Sample selection bias as a specification error,” Eco… (1979) Sample selection bias as a specification error | 0.737 | 3 | 2 | 100% |
| 2 | H. Ichimura, “Semiparametric least squares (sls) and weighted sls es… (1993) Semiparametric least squares (sls) and weighted sls estimation of single-index models | 0.737 | 3 | 2 | 100% |
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Showing the top 10 of 49 scored citations.