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Journal articles on the topic 'Partial likelihood (Statistics)'

Author: Grafiati

Published: 4 June 2021

Last updated: 7 February 2022

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1

Broström, Göran, and Marie Lindkvist. "Partial Partial Likelihood." Communications in Statistics - Simulation and Computation 37, no. 4 (2008): 679–86. http://dx.doi.org/10.1080/03610910701884021.

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2

Wang, Qi-Hua, and Bing-Yi Jing. "Empirical likelihood for partial linear models." Annals of the Institute of Statistical Mathematics 55, no. 3 (2003): 585–95. http://dx.doi.org/10.1007/bf02517809.

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3

Chan, Schultz, and Malay Ghosh. "A geometric optimally of Cox's partial likelihood." Canadian Journal of Statistics 27, no. 2 (1999): 315–20. http://dx.doi.org/10.2307/3315641.

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4

Fan, Jianqing, Huazhen Lin, and Yong Zhou. "Local partial-likelihood estimation for lifetime data." Annals of Statistics 34, no. 1 (2006): 290–325. http://dx.doi.org/10.1214/009053605000000796.

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5

Yip, Paul S. F., and Qizhi Chen. "A Partial Likelihood Estimator of Vaccine Efficacy." Australian & New Zealand Journal of Statistics 42, no. 3 (2000): 367–74. http://dx.doi.org/10.1111/1467-842x.00133.

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6

Slud, Eric V. "Inefficiency of inferences with the partial likelihood." Communications in Statistics - Theory and Methods 15, no. 11 (1986): 3333–51. http://dx.doi.org/10.1080/03610928608829314.

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7

Kim, Yongdai, and Dohyun Kim. "Bayesian partial likelihood approach for tied observations." Journal of Statistical Planning and Inference 139, no. 2 (2009): 469–77. http://dx.doi.org/10.1016/j.jspi.2008.05.008.

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8

Qin, Gengsheng, and Bing-Yi Jing. "Censored Partial Linear Models and Empirical Likelihood." Journal of Multivariate Analysis 78, no. 1 (2001): 37–61. http://dx.doi.org/10.1006/jmva.2000.1944.

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9

Taylor, Julian D., and Arūnas P. Verbyla. "ASYMPTOTIC LIKELIHOOD APPROXIMATIONS USING A PARTIAL LAPLACE APPROXIMATION." Australian & New Zealand Journal of Statistics 48, no. 4 (2006): 465–76. http://dx.doi.org/10.1111/j.1467-842x.2006.00451.x.

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10

Chen, Songnian, and Lingzhi Zhou. "Local partial likelihood estimation in proportional hazards regression." Annals of Statistics 35, no. 2 (2007): 888–916. http://dx.doi.org/10.1214/009053606000001299.

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11

Chen, Kani, Shaojun Guo, Liuquan Sun, and Jane-Ling Wang. "Global Partial Likelihood for Nonparametric Proportional Hazards Models." Journal of the American Statistical Association 105, no. 490 (2010): 750–60. http://dx.doi.org/10.1198/jasa.2010.tm08636.

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12

van de Geer, Sara, and Enno Mammen. "Penalized quasi-likelihood estimation in partial linear models." Annals of Statistics 25, no. 3 (1997): 1014–35. http://dx.doi.org/10.1214/aos/1069362736.

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13

Rüschendorf, Ludger, and M. Riedel. "Stochastic Ordering of Likelihood Ratios and Partial Sufficiency." Statistics 22, no. 4 (1991): 551–58. http://dx.doi.org/10.1080/02331889108802337.

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14

Fan, Guo-Liang, Han-Ying Liang, and Hong-Xia Xu. "Empirical Likelihood for a Heteroscedastic Partial Linear Model." Communications in Statistics - Theory and Methods 40, no. 8 (2011): 1396–417. http://dx.doi.org/10.1080/03610921003597229.

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15

Jacod, Jean. "Partial likelihood process and asymptotic normality." Stochastic Processes and their Applications 26 (1987): 47–71. http://dx.doi.org/10.1016/0304-4149(87)90050-0.

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16

Gu, Minggao, Yueqin Wu, and Bin Huang. "Partial marginal likelihood estimation for general transformation models." Journal of Multivariate Analysis 123 (January 2014): 1–18. http://dx.doi.org/10.1016/j.jmva.2013.08.016.

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17

Sasieni, Peter. "Maximum Weighted Partial Likelihood Estimators for the Cox Model." Journal of the American Statistical Association 88, no. 421 (1993): 144. http://dx.doi.org/10.2307/2290707.

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18

SUN, YANQING, RAJESHWARI SUNDARAM, and YICHUAN ZHAO. "Empirical Likelihood Inference for the Cox Model with Time-dependent Coefficients via Local Partial Likelihood." Scandinavian Journal of Statistics 36, no. 3 (2009): 444–62. http://dx.doi.org/10.1111/j.1467-9469.2008.00634.x.

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19

Purhadi, Purhadi, and M. Fathurahman. "A Logit Model for Bivariate Binary Responses." Symmetry 13, no. 2 (2021): 326. http://dx.doi.org/10.3390/sym13020326.

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This article provides a bivariate binary logit model and statistical inference procedures for parameter estimation and hypothesis testing. The bivariate binary logit (BBL) model is an extension of the binary logit model that has two correlated binary responses. The BBL model responses were formed using a 2 × 2 contingency table, which follows a multinomial distribution. The maximum likelihood and Berndt–Hall–Hall–Hausman (BHHH) methods were used to obtain the BBL model. Hypothesis testing of the BBL model contains the simultaneous test and the partial test. The test statistics of the simultane

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20

Zou, F. "A note on a partial empirical likelihood." Biometrika 89, no. 4 (2002): 958–61. http://dx.doi.org/10.1093/biomet/89.4.958.

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21

Sinha, D. "A Bayesian justification of Cox's partial likelihood." Biometrika 90, no. 3 (2003): 629–41. http://dx.doi.org/10.1093/biomet/90.3.629.

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22

Provost, Serge B. "Likelihood ratio test for independence with partial multivariate normal data." Communications in Statistics - Theory and Methods 17, no. 6 (1988): 1763–75. http://dx.doi.org/10.1080/03610928808829712.

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23

López-Fidalgo, J., and M. J. Rivas-López. "Optimal experimental designs for partial likelihood information." Computational Statistics & Data Analysis 71 (March 2014): 859–67. http://dx.doi.org/10.1016/j.csda.2012.10.009.

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24

Fokianos, Konstantinos, and Benjamin Kedem. "Partial Likelihood Inference For Time Series Following Generalized Linear Models." Journal of Time Series Analysis 25, no. 2 (2004): 173–97. http://dx.doi.org/10.1046/j.0143-9782.2003.00344.x.

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25

Chen, Xia, and Hengjian Cui. "Empirical likelihood inference for partial linear models under martingale difference sequence." Statistics & Probability Letters 78, no. 17 (2008): 2895–901. http://dx.doi.org/10.1016/j.spl.2008.04.012.

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26

Cruz, F. R. B., E. A. Colosimo, and J. MacGregor Smith. "Sample Size Corrections for the Maximum Partial Likelihood Estimator." Communications in Statistics - Simulation and Computation 33, no. 1 (2004): 35–47. http://dx.doi.org/10.1081/sac-120028432.

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27

Sumner, J. G., and M. A. Charleston. "Phylogenetic estimation with partial likelihood tensors." Journal of Theoretical Biology 262, no. 3 (2010): 413–24. http://dx.doi.org/10.1016/j.jtbi.2009.09.037.

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28

LOK, JUDITH J. "Structural Nested Models and Standard Software: A Mathematical Foundation through Partial Likelihood." Scandinavian Journal of Statistics 34, no. 1 (2007): 186–206. http://dx.doi.org/10.1111/j.1467-9469.2006.00539.x.

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29

Zucker, David M. "A Pseudo–Partial Likelihood Method for Semiparametric Survival Regression With Covariate Errors." Journal of the American Statistical Association 100, no. 472 (2005): 1264–77. http://dx.doi.org/10.1198/016214505000000538.

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30

Trivedi, P. K., and J. N. Alexander. "Reemployment Probability and Multiple Unemployment Spells: A Partial-Likelihood Approach." Journal of Business & Economic Statistics 7, no. 3 (1989): 395. http://dx.doi.org/10.2307/1391536.

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31

de Lima, Igo Pedro, Sérgio Luiz E. F. da Silva, Gilberto Corso, and João M. de Araújo. "Tsallis Entropy, Likelihood, and the Robust Seismic Inversion." Entropy 22, no. 4 (2020): 464. http://dx.doi.org/10.3390/e22040464.

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The nonextensive statistical mechanics proposed by Tsallis have been successfully used to model and analyze many complex phenomena. Here, we study the role of the generalized Tsallis statistics on the inverse problem theory. Most inverse problems are formulated as an optimisation problem that aims to estimate the physical parameters of a system from indirect and partial observations. In the conventional approach, the misfit function that is to be minimized is based on the least-squares distance between the observed data and the modelled data (residuals or errors), in which the residuals are as

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32

Goldstein, Larry, and Haimeng Zhang. "Efficiency of the maximum partial likelihood estimator for nested case control sampling." Bernoulli 15, no. 2 (2009): 569–97. http://dx.doi.org/10.3150/08-bej162.

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33

Zheng, Ming, and Sihua Li. "Empirical Likelihood in Partial Linear Error-in-Covariable Model with Censored Data." Communications in Statistics - Theory and Methods 34, no. 2 (2005): 389–404. http://dx.doi.org/10.1080/03610920509342428.

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34

Pang, Guofei, and Wanrong Cao. "Pseudo-Likelihood Estimation for Parameters of Stochastic Time-Fractional Diffusion Equations." Fractal and Fractional 5, no. 3 (2021): 129. http://dx.doi.org/10.3390/fractalfract5030129.

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Although stochastic fractional partial differential equations have received increasing attention in the last decade, the parameter estimation of these equations has been seldom reported in literature. In this paper, we propose a pseudo-likelihood approach to estimating the parameters of stochastic time-fractional diffusion equations, whose forward solver has been investigated very recently by Gunzburger, Li, and Wang (2019). Our approach can accurately recover the fractional order, diffusion coefficient, as well as noise magnitude given the discrete observation data corresponding to only one r

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35

MURPHY, SUSAN, and BING LI. "Projected partial likelihood and its application to longitudinal data." Biometrika 82, no. 2 (1995): 399–406. http://dx.doi.org/10.1093/biomet/82.2.399.

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36

Qin, Guoyou, Yang Bai, and Zhongyi Zhu. "Robust empirical likelihood inference for generalized partial linear models with longitudinal data." Journal of Multivariate Analysis 105, no. 1 (2012): 32–44. http://dx.doi.org/10.1016/j.jmva.2011.08.003.

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37

Lin, Huazhen, Ye He, and Jian Huang. "A global partial likelihood estimation in the additive Cox proportional hazards model." Journal of Statistical Planning and Inference 169 (February 2016): 71–87. http://dx.doi.org/10.1016/j.jspi.2015.08.002.

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38

Hauser, Russ, Hua Liang, John D. Meeker, Haiyan Su, and Sally W. Thurston. "Empirical likelihood based inference for additive partial linear measurement error models." Statistics and Its Interface 2, no. 1 (2009): 83–90. http://dx.doi.org/10.4310/sii.2009.v2.n1.a8.

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39

Zhang, Haimeng, and M. Bhaskara Rao. "A note on the generalized maximum likelihood estimator in partial Koziol–Green model." Statistics & Probability Letters 76, no. 8 (2006): 813–20. http://dx.doi.org/10.1016/j.spl.2005.10.032.

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40

Nagashima, Kengo, and Yasunori Sato. "Information criteria for Firth's penalized partial likelihood approach in Cox regression models." Statistics in Medicine 36, no. 21 (2017): 3422–36. http://dx.doi.org/10.1002/sim.7368.

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41

Zhang, Biao. "A Partial Empirical Likelihood Based Score Test Under a Semiparametric Finite Mixture Model." Annals of the Institute of Statistical Mathematics 58, no. 4 (2006): 707–19. http://dx.doi.org/10.1007/s10463-006-0043-y.

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42

Wang, Ji-Ping, and Bruce G. Lindsay. "An exponential partial prior for improving nonparametric maximum likelihood estimation in mixture models." Statistical Methodology 5, no. 1 (2008): 30–45. http://dx.doi.org/10.1016/j.stamet.2007.03.004.

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43

Kim, Yoon Tae, and Hyun Suk Park. "Convergence rate of maximum likelihood estimator of parameter in stochastic partial differential equation." Journal of the Korean Statistical Society 44, no. 2 (2015): 312–20. http://dx.doi.org/10.1016/j.jkss.2015.01.001.

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44

Konecny, Foranz. "Maximum likelihood estimation for doubly stochastic poisson processes with partial observations." Stochastics 16, no. 1-2 (1986): 51–63. http://dx.doi.org/10.1080/17442508608833366.

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45

Sirén, Jukka, and Samuel Kaski. "Local dimension reduction of summary statistics for likelihood-free inference." Statistics and Computing 30, no. 3 (2019): 559–70. http://dx.doi.org/10.1007/s11222-019-09905-w.

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Abstract Approximate Bayesian computation (ABC) and other likelihood-free inference methods have gained popularity in the last decade, as they allow rigorous statistical inference for complex models without analytically tractable likelihood functions. A key component for accurate inference with ABC is the choice of summary statistics, which summarize the information in the data, but at the same time should be low-dimensional for efficiency. Several dimension reduction techniques have been introduced to automatically construct informative and low-dimensional summaries from a possibly large pool

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46

Eğecioğlu, Ömer, and Ayça Ebru Giritligil. "The Likelihood of Choosing the Borda-Winner With Partial Preference Rankings of the Electorate." Journal of Modern Applied Statistical Methods 10, no. 1 (2011): 349–61. http://dx.doi.org/10.22237/jmasm/1304224260.

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47

Doksum, Kjell A. "An Extension of Partial Likelihood Methods for Proportional Hazard Models to General Transformation Models." Annals of Statistics 15, no. 1 (1987): 325–45. http://dx.doi.org/10.1214/aos/1176350269.

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48

Xu, Da, and Yong Zhou. "Local composite partial likelihood estimation for length-biased and right-censored data." Journal of Statistical Computation and Simulation 89, no. 14 (2019): 2661–77. http://dx.doi.org/10.1080/00949655.2019.1628963.

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49

Ha, Il Do, Nicholas J. Christian, Jong-Hyeon Jeong, Junwoo Park, and Youngjo Lee. "Analysis of clustered competing risks data using subdistribution hazard models with multivariate frailties." Statistical Methods in Medical Research 25, no. 6 (2016): 2488–505. http://dx.doi.org/10.1177/0962280214526193.

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Competing risks data often exist within a center in multi-center randomized clinical trials where the treatment effects or baseline risks may vary among centers. In this paper, we propose a subdistribution hazard regression model with multivariate frailty to investigate heterogeneity in treatment effects among centers from multi-center clinical trials. For inference, we develop a hierarchical likelihood (or h-likelihood) method, which obviates the need for an intractable integration over the frailty terms. We show that the profile likelihood function derived from the h-likelihood is identical

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50

Yang, Ming, Gideon K. D. Zamba, and Joseph E. Cavanaugh. "Markov regression models for count time series with excess zeros: A partial likelihood approach." Statistical Methodology 14 (September 2013): 26–38. http://dx.doi.org/10.1016/j.stamet.2013.02.001.

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