Semiparametric Correction for Endogenous Truncation Bias With Vox Populi-Based Participation Decision

We synthesize the knowledge present in various scientific disciplines for the development of the semiparametric endogenous truncation-proof algorithm, correcting for truncation bias due to endogenous self-selection. This synthesis enriches the algorithm’s accuracy, efficiency, and applicability. Improving upon the covariate shift assumption, data are intrinsically affected and largely generated by their own behavior (cognition). Refining the concept of Vox Populi (Wisdom of Crowd) allows data points to sort themselves out depending on their estimated latent reference group opinion space. Monte Carlo simulations, based on 2 000 000 different distribution functions, practically generating 100 million realizations, attest to a very high accuracy of our model.

• Publication year

  2019

• Venue

  IEEE Access

• Publication date

  2019-02-17

• Fields of study

  Computer Science, Economics, Political Science

• Identifiers
  DOI 10.1109/ACCESS.2018.2888575arXiv 1902.06286
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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