Journal of Guangxi Normal University(Natural Science Edition) ›› 2022, Vol. 40 ›› Issue (1): 108-124.doi: 10.16088/j.issn.1001-6600.2021060909
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REN Shuai, CHENG Wenhui, ZHOU Jie*
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| [1] HASTIE T, TIBSHIRANI R. Generalized additive models[J]. Boca Raton: Chapman and Hall/CRC, Statistics 1990. [2] HECKMAN N E. Spline smoothing in a partly linear model[J]. Journal of the Royal Statistical Society, 1986, 48(2): 244-248. [3] SPECKMAN P. Kernel smoothing in partial linear model[J]. Journal of the Royal Statistical Society Series B: Methodological, 1988, 50(3): 413-436. [4]ROBINSON P M. Root-N-consistent semiparametric regression[J]. Econometrica, 1988, 56(4): 931-954. [5]CHEN H. Convergence rates for parametric components in a partly linear model[J]. The Annals of Statistics, 1988, 16 (1): 136-146. [6]CHEN H, SHIAU J. A two-stage spline smoothing method for partially linear models[J]. Journal of Statistical Planning & Inference, 1991, 27(2): 187-201. [7]LI Q. Efficient estimation of additive partially linear models[J]. Biometrika, 2002, 89(1): 39-48. [8] FAN Y, LI Q. A kernel-based method for estimating additive partially linear models[J]. Statistica Sinica, 2003, 13(3): 739-762. [9]MA S, YANG L. Spline-backfitted kernel smoothing of partially linear additive model[J]. Journal of Statistical Planning & Inference, 2011, 141(1): 204-219. [10]WANG L, LIU X, LIANG H. Estimation and variable selection for generalized additive partial linear models[J]. The Annals of Statistics, 2011, 39(4): 1827-1851. [11]黄四民, 梁华. 用半参数部分线性模型分析居民消费结构[J]. 数量经济技术经济研究, 1994(10): 33-38. [12]李启华, 蓝志青, 邢雅康. 基于半参数估计的笔记本电脑特征价格指数研究[J]. 东北财经大学学报, 2011(2): 83-83. [13]NEWCOMB S. A generalized theory of the combination of observations so as to obtain the best result[J]. American Journal of Mathematics, 1886, 8(4): 343-366. [14]PEARSON K. Contributions to the mathematical theory of evolution[J]. Journal of the Royal Statistical Society, 1893, 56(4): 675-679. [15]BÖHNING D. A review of reliable maximum likelihood algorithms for semiparametric mixture models[J]. Journal of Statistical Planning & Inference, 1995, 47(1/2): 5-28. [16]BILMES J A. A gentle tutorial of the em algorithm and its application to parameter estimation for Gaussian mixture and hidden Markov models[R]. California: International Computer Science Institute, 2000. [17]FIGUEIREDO M A T, JAIN A K. Unsupervised learning of finite mixture models[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2002, 24(3): 381-396. [18]YIN J T, ZHANG Y F, GAO L X. Accelerating distributed expectation-maximization algorithms with frequent updates[J]. Journal of Parallel & Distributed Computing, 2018, 111(1): 65-75. [19]马晓敏, 贾卫东, 杨朔, 等. 有限混合模型在肝硬化住院患者医疗费用研究中的应用[J]. 中国卫生统计, 2017,34(3):412-414. [20]JANSEN R C. Maximum likelihood in a generalized linear finite mixture model by using the EM algorithm[J].Biometrics, 1993, 49(1): 227-31. [21]WEDEL M, DESARBO W S. A mixture likelihood approach for generalized linear models[J]. Journal of Classification, 1995, 12(1): 21-55. [22] YOUNG D S, HUNTER D R. Mixtures of regressions with predictor-dependent mixing proportions[J]. Computational Statistics & Data Analysis, 2010, 54(10): 2253-2266. [23]HUANG M, YAO W. Mixture of regression models with varying mixing proportions: A semiparametric approach[J]. Journal of the American Statistical Association, 2012, 107(498):711-724. [24]WU X, YU C. Estimation of the mixtures of GLMs with covariate-dependent mixing proportions[J]. Communications in Statistics-Theory and Methods, 2016, 45(24): 7242-7257. [25]CAO J, YAO W. Semiparametric mixture of binomial regression with a degenerate component[J]. Statistica Sinica, 2012, 22(1): 27-46. [26]HUANG M, LI R Z, WANG S L. Nonparametric mixture of regression models[J]. Journal of the American Statistical Association, 2013, 108: 929-941. [27]WANG S, YAO W, HUANG M. A note on the identifiability of nonparametric and semiparametric mixtures of GLMs[J]. Statistics & Probability Letters, 2014, 93: 41-45. [28]XIANG S J, YAO W X. Semiparametric mixtures of regressions with single-index for model based clustering[J]. Advances in Data Analysis and Classification, 2020(14): 261-292. [29]TITTERINGTON D M, SMITH A, Makov U E. Statistical analysis of finite mixture distributions[J]. Biometrics, 1986, 42(3): 679-680. [30]HENNIG C. Identifiablity of models for clusterwise linear regression[J]. Journal of Classification, 2000, 17(2): 273-296. [31]JENSEN D R. Mixture models: Theory, geometry and applications[J]. Journal of Statistical Planning & Inference, 1997, 59(1): 179-181. [32]LI Q, WOOLDRIDGE J M. Semiparametric estimation of partially linear models for dependent data with generated regressors[J]. Econometric Theory, 2002, 18(3),625-645. [33]ZHANG Y, PAN W Q. Estimation and inference for mixture of partially linear additive models[J//OL]. Communications in Statistics-Theory and Methods, 2020. [2021-06-09]. https://www.tandfonline/doi/full/10.1080103610926.2020.1777035. [34]CLAESKENS G, KEILEGOM I V. Bootstrap confidence bands for regression curves and their derivatives[J]. The Annals of Statistics, 2003, 31(6): 1852-1884. [35]FAN J Q, GIJBELS I. Local polynomial modelling and its applications: Monographs on statistics and applied probability[M]. Boca Raton: Chapman and Hall/CRC, 1996. [36]BOOR C D. A practical guide to splines (Applied Mathematical Sciences)[M]. New York: Springer, 1978: 27. [37]LI R, LIANG H. Variable selection in semiparametric regression modeling[J]. The Annals of Statistics, 2008, 36(1): 261-286. |
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