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Journals / Hacettepe Journal of Mathematics and Statistics / 2026 / Volume: 42 Issue: 2

Multivariate Estimation from "Two Variables at a Time" Observations

Christopher S. Withers
Saralees Nadarajah
Pages
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Publication Date
2013-02-01
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

We give both nonparametric estimates and the maximum likelihood estimates (MLEs) undernormality, and their covariances.

📌 3 Key Takeaways

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Objective & Hypothesis:Suppose that we wish to estimate the mean µ and the covariance Cof a random p-vector X with p > 2, but we can only sample from thevector X two of its p components at a time.
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Key Findings & Data:Suppose that we wish to estimate the mean µ and the covariance Cof a random p-vector X with p > 2, but we can only sample from thevector X two of its p components at a time.
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Conclusion & Impact:We give both nonparametric estimates and the maximum likelihood estimates (MLEs) undernormality, and their covariances.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Maximum likelihood estimation · Multivariate normal · Nonparametric estimation

Abstract

Suppose that we wish to estimate the mean µ and the covariance Cof a random p-vector X with p > 2, but we can only sample from thevector X two of its p components at a time. We give both nonparametric estimates and the maximum likelihood estimates (MLEs) undernormality, and their covariances.

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Cite This Article

Withers, C. S., Nadarajah, S. (2013). Multivariate Estimation from "Two Variables at a Time" Observations. Hacettepe Journal of Mathematics and Statistics, Volume: 42 Issue: 2. https://ajindex.com/articles/1403491

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References (7)

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