Academia Sinica, Institute of Statistical Science | Taiwan
Prof. Gwo Dong Lin is a distinguished statistician and mathematician whose extensive contributions have profoundly influenced the fields of probability theory, moment problems, and life distribution analysis. With an h-index of 18, 71 published documents, and 933 citations from 783 sources, his scholarly output demonstrates both depth and enduring impact. He earned his Ph.D. in Management Science from Tamkang University, following earlier degrees in mathematics from National Taiwan Normal University. Over his career, Prof. Lin served at Academia Sinica’s Institute of Statistical Science, including roles as Deputy Director and Acting Director, and later as Adjunct Research Fellow. He has also directed the Social and Data Science Research Center under the Hwa-Kang Xing-Ye Foundation. His editorial work spans several international journals, and he has been an invited speaker at global conferences organized by the International Statistical Institute and other leading organizations. Recognized as an ISI Elected Member since 1991 and recipient of Taiwan’s Outstanding Research Award (1994–1995), Prof. Lin’s pioneering studies on characterizations of distributions, inequalities for transforms, and moment determinacy continue to shape modern statistical theory and inspire future explorations in applied probability and statistical modeling.
Profile : Scopus
Featured Publications
Lin, G. D., & Stoyanov, J. (2025). New sufficient conditions for moment-determinacy via probability density tails. Mathematics, 13, 2671.
Dou, X., Kuriki, S., Lin, G. D., & Richards, D. (2025). EM estimation of the B-spline copula with penalized pseudo-likelihood functions. Statistical Papers, 66, 30.
Lin, G. D., & Stoyanov, J. (2024). New characterizations of the Gamma distribution via independence of two statistics by using Anosov’s theorem. Theory of Probability and Its Applications, 69, 745–759 (Russian edition); SIAM version, 69, 592–604.
Hu, C.-Y., & Lin, G. D. (2022). Characterizations of the normal distribution via the independence of the sample mean and the feasible definite statistics with ordered arguments. Annals of the Institute of Statistical Mathematics, 74, 473–488.
Lin, G. D., & Hu, C.-Y. (2022). On the semi-Mittag-Leffler distributions. Probability and Mathematical Statistics, 42, 81–96.
Hu, C.-Y., Lin, G. D., & Stoyanov, J. (2021). Characterization of probability distributions via functional equations of power-mixture type. Mathematics, 9, 271. Also in: L. Shaikhet (Ed.), Prime Archives in Applied Mathematics (2nd ed.). Hyderabad, India: Vide Leaf.
Lin, G. D., & Dou, X. (2021). An identity for two integral transforms applied to the uniqueness of a distribution via its Laplace–Stieltjes transform. Statistics, 55, 365–385.
Dou, X., Kuriki, S., Lin, G. D., & Richards, D. (2021). Dependence structures of B-spline copulas. Sankhyā: The Indian Journal of Statistics, Series A, 83, 238–311.
Lin, G. D., & Hu, C.-Y. (2021). Formulas of absolute moments. Sankhyā: The Indian Journal of Statistics, Series A, 83, 476–495.
Hu, C.-Y., & Lin, G. D. (2020). Necessary and sufficient conditions for unique solution to functional equations of Poincaré type. Journal of Mathematical Analysis and Applications, 491, 124399.
Stoyanov, J. M., Lin, G. D., & Kopanov, P. (2020). New checkable conditions for moment determinacy of probability distributions. Theory of Probability and Its Applications, 65, 634–648 (Russian edition); SIAM version, 65, 497–509.
Lin, G. D., Dou, X., & Kuriki, S. (2019). The bivariate lack-of-memory distributions. Sankhyā: The Indian Journal of Statistics, Series A, 81, 273–297.
Lin, G. D. (2019). On powers of the Catalan number sequence. Discrete Mathematics, 342, 2139–2147.
Hu, C.-Y., & Lin, G. D. (2018). Characterizations of the logistic and related distributions. Journal of Mathematical Analysis and Applications, 463, 79–92.
Lin, G. D. (2017). Recent developments on the moment problem. Journal of Statistical Distributions and Applications, 4, 5.
Lai, C.-D., Lin, G. D., Govindaraju, K., & Pirikahu, S. (2017). A simulation study on the correlation structure of Marshall–Olkin bivariate Weibull distribution. Journal of Statistical Computation and Simulation, 87, 156–170.