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Dergiler / Hacettepe Journal of Mathematics and Statistics / 2026 / Volume: 49 Issue: 4

Adaptive thresholding estimator for differential association structures in two independent contingency tables

Seyed Kamran Ghoreishi(University of Qom)0000-0003-4998-6707
Jingjing Wu(University of Calgary)0000-0003-4555-1490
Sayfa
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Yayın Tarihi
2020-08-06
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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

In this line, we carry out a simulation study and compare two well-known independent social mobility datasets.

📌 3 Maddede Bu Makale

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Amaç & Hipotez:In this paper, we consider an adaptive thresholding procedure to estimate the difference of association structures in two independent two-way contingency tables of the same order.
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Temel Bulgular & Veri:Under $L_1$ and $L_2$ loss functions, we establish the corresponding risk's upper bounds for our differential association adaptive thresholding estimators.
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Sonuç & Katkı:In this line, we carry out a simulation study and compare two well-known independent social mobility datasets.
🔬Tür:Research Article
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Association orthogonal components · Intrinsic association parameters · Adaptive thresholding estimator

Abstract

In this paper, we consider an adaptive thresholding procedure to estimate the difference of association structures in two independent two-way contingency tables of the same order. Here, we assume that the class of paired association structures have an approximately sparse difference. Under $L_1$ and $L_2$ loss functions, we establish the corresponding risk's upper bounds for our differential association adaptive thresholding estimators. Moreover, we show that these estimators perform well in a simulated setting. In this line, we carry out a simulation study and compare two well-known independent social mobility datasets.

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Bu Makaleye Atıf Yap

Ghoreishi, S. K., Wu, J. (2020). Adaptive thresholding estimator for differential association structures in two independent contingency tables. Hacettepe Journal of Mathematics and Statistics, Volume: 49 Issue: 4. https://doi.org/10.15672/hujms.560405

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