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Nonparametric inference for quantile cointegrations with stationary covariates.

• Authors : Tu, Yundong; Liang, Han-Ying; Wang, Qiying

• Source: Journal of Econometrics. 2022, Vol. 230, Issue 2, pages. 453

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Quantile regression for varying-coefficient partially nonlinear models with randomly truncated data.

• Authors : Xu, Hong-Xia; Fan, Guo-Liang; Liang, Han-Ying

Subjects: QUANTILE regression; LIKELIHOOD ratio tests; DISTRIBUTION (Probability theory)

• Source: Statistical Papers; Jun2024, Vol. 65 Issue 4, p2567-2604, 38p

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Quantile difference estimation with censoring indicators missing at random.

• Authors : Kong, Cui-Juan; Liang, Han-Ying

Subjects: ASYMPTOTIC distribution; ASYMPTOTIC normality; MAXIMUM likelihood statistics

• Source: Lifetime Data Analysis; Apr2024, Vol. 30 Issue 2, p345-382, 38p

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Applied Science & Technology Full Text (H.W. Wilson)

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Applied Science & Technology Full Text (H.W. Wilson)

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Functional regression with dependent error and missing observation in reproducing kernel Hilbert spaces.

• Authors : Hu, Yan-Ping; Liang, Han-Ying

• Source: Journal of the Korean Statistical Society; Sep2023, Vol. 52 Issue 3, p736-764, 29p

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Quantile Regression of Ultra-high Dimensional Partially Linear Varying-coefficient Model with Missing Observations.

• Authors : Wang, Bao Hua; Liang, Han Ying

Subjects: MISSING data (Statistics); QUANTILE regression; ASYMPTOTIC normality

• Source: Acta Mathematica Sinica; Sep2023, Vol. 39 Issue 9, p1701-1726, 26p

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Bayesian empirical likelihood of quantile regression with missing observations.

• Authors : Liu, Chang-Sheng; Liang, Han-Ying

Subjects: MISSING data (Statistics); QUANTILE regression; MARKOV chain Monte Carlo

• Source: Metrika; Apr2023, Vol. 86 Issue 3, p285-313, 29p

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Agricola

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Local likelihood of quantile difference under left-truncated, right-censored and dependent assumptions.

• Authors : Kong, Cui-Juan; Liang, Han-Ying; Fan, Guo-Liang

Subjects: DISTRIBUTION (Probability theory); ASYMPTOTIC normality; MAXIMUM likelihood statistics

• Source: Statistics; Feb2023, Vol. 57 Issue 1, p71-93, 23p

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