[1] |
Adimari, G., & Chiogna, M. (2012). Jackknife empirical likelihood based confidence intervals for partial areas under ROC curves. Statistica Sinica, 22, 1457-1477. · Zbl 1534.62059 |
[2] |
Alemdjrodo, K., & Zhao, Y. (2019). Reduce the computation in jackknife empirical likelihood for comparing two correlated Gini indices. Journal of Nonparametric Statistics, 31, 849-866. · Zbl 1432.62066 |
[3] |
Alemdjrodo, K., & Zhao, Y. (2020). New empirical likelihood inference for the mean residual life with length‐biased and right‐censored data. Journal of Nonparametric Statistics, 32, 1029-1046. · Zbl 1466.62273 |
[4] |
Alemdjrodo, K., & Zhao, Y. (2022). Novel empirical likelihood inference for the mean difference with right‐censored data. Statistical Methods in Medical Research, 31, 87-104. |
[5] |
An, Y., & Zhao, Y. (2018). Jackknife empirical likelihood for the difference of two volumes under ROC surfaces. Annals of the Institute of Statistical Mathematics, 70, 789-806. · Zbl 1406.62132 |
[6] |
Anatolyev, S. (2005). GMM, GEL, serial correlation, and asymptotic bias. Econometrica, 73, 983-1002. · Zbl 1152.62360 |
[7] |
Bartolucci, F. (2007). A penalized version of the empirical likelihood ratio for the population mean. Statistics & Probability Letters, 77, 104-110. · Zbl 1106.62050 |
[8] |
Bedoui, A., & Lazar, N. A. (2020). Bayesian empirical likelihood for ridge and lasso regressions. Computational Statistics and Data Analysis, 145, 106917. · Zbl 1510.62307 |
[9] |
Berger, Y. G. (2015). An R library to construct empirical likelihood confidence intervals for complex estimators. In New techniques and technologies for statistics. Statistical Sciences Research Institute. |
[10] |
Berger, Y. G., & Torres, O. D. L. R. (2016). Empirical likelihood confidence intervals for complex sampling designs. Journal of the Royal Statistical Society. Series B (Statistical Methodology), 78, 319-341. · Zbl 1414.62046 |
[11] |
Bouadoumou, M., Zhao, Y., & Lu, Y. (2015). Jackknife empirical likelihood for the accelerated failure time model with censored data. Communications in Statistics—Simulation and Computation, 44, 1818-1832. · Zbl 1327.62484 |
[12] |
Bravo, F., Escanciano, J. C., & Keilegom, I. V. (2020). Two‐step semiparametric empirical likelihood inference. The Annals of Statistics, 48, 1-26. · Zbl 1439.62188 |
[13] |
Bühlmann, P., & Geer, S. v. d. (2011). Statistics for high‐dimensional data: Methods, theory and applications. Springer. · Zbl 1273.62015 |
[14] |
Cappé, O., Garivier, A., Maillard, O.‐A., Munos, R., & Stoltz, G. (2013). Kullback‐leibler upper confidence bounds for optimal sequential allocation. The Annals of Statistics, 41, 1516-1541. · Zbl 1293.62161 |
[15] |
Chang, J., Chen, S. X., & Chen, X. (2015). High dimensional generalized empirical likelihood for moment restrictions with dependent data. Journal of Econometrics, 185, 283-304. · Zbl 1331.62188 |
[16] |
Chang, J., Chen, S. X., Tang, C. Y., & Wu, T. T. (2021). High‐dimensional empirical likelihood inference. Biometrika, 108, 127-147. · Zbl 1462.62760 |
[17] |
Chang, J., Tang, C. Y., & Wu, T. T. (2018). A new scope of penalized empirical likelihood with high‐dimensional estimating equations. The Annals of Statistics, 46, 3185-3216. · Zbl 1408.62053 |
[18] |
Chaudhuri, S., & Ghosh, M. (2011). Empirical likelihood for small area estimation. Biometrika, 98, 473-480. · Zbl 1215.62031 |
[19] |
Chaudhuri, S., Mondal, D., & Yin, T. (2017). Hamiltonian Monte Carlo sampling in Bayesian empirical likelihood computation. Journal of the Royal Statistical Society: Series B, 79, 293-320. · Zbl 1414.62333 |
[20] |
Chaussé, P. (2010). Computing generalized method of moments and generalized empirical likelihood with R. Journal of Statistical Software, 34, 1-35. |
[21] |
Chen, B., Pan, G., Yang, Q., & Zhou, W. (2015). Large dimensional empirical likelihood. Statistica Sinica, 25, 1659-1677. · Zbl 1377.62127 |
[22] |
Chen, J., & Huang, Y. (2013). Finite‐sample properties of the adjusted empirical likelihood. Journal of Nonparametric Statistics, 25, 147-159. · Zbl 1297.62105 |
[23] |
Chen, J., & Liu, Y. (2012). Adjusted empirical likelihood with high‐order one‐sided coverage precision. Statistics and its Interface, 5, 281-292. · Zbl 1383.62141 |
[24] |
Chen, J., Variyath, A. M., & Abraham, B. (2008). Adjusted empirical likelihood and its properties. Journal of Computational and Graphical Statistics, 17, 426-443. |
[25] |
Chen, S. (1993). On the accuracy of empirical likelihood confidence regions for linear regression model. Annals of the Institute of Statistical Mathematics, 45, 621-637. · Zbl 0799.62070 |
[26] |
Chen, S., & Cui, H. (2006). On Bartlett correction of empirical likelihood in the presence of nuisance parameters. Biometrika, 93, 215-220. · Zbl 1152.62325 |
[27] |
Chen, S., & Cui, H. (2007). On the second‐order properties of empirical likelihood with moment restrictions. Journal of Econometrics, 141, 492-516. · Zbl 1407.62157 |
[28] |
Chen, S., & Hall, P. (1993). Smoothed empirical likelihood confidence intervals for quantiles. The Annals of Statistics, 21, 1166-1181. · Zbl 0786.62053 |
[29] |
Chen, S., & Haziza, D. (2018). Jackknife empirical likelihood method for multiply robust estimation with missing data. Computational Statistics and Data Analysis, 127, 258-268. · Zbl 1469.62042 |
[30] |
Chen, S., Peng, L., & Qin, Y.‐L. (2009). Effects of data dimension on empirical likelihood. Biometrika, 96, 711-722. · Zbl 1170.62023 |
[31] |
Chen, S., Zhao, Y., & Wang, Y. (2021). Sample empirical likelihood approach under complex survey design with scrambled responses. Survey Methodology, 47, 59-74. |
[32] |
Chen, S. X., & Keilegom, I. V. (2009). A review on empirical likelihood methods for regression. TEST, 18, 415-447. · Zbl 1203.62035 |
[33] |
Chen, Y.‐J., Ning, W., & Gupta, A. K. (2015). Jackknife empirical likelihood method for testing the equality of two variances. Journal of Applied Statistics, 42, 144-160. · Zbl 1514.62488 |
[34] |
Cheng, C., Liu, Y., Liu, Z., & Zhou, W. (2018). Balanced augmented jackknife empirical likelihood for two sample U‐statistics. Science China Mathematics, 61, 1129-1138. · Zbl 1394.62051 |
[35] |
Cheng, Y., & Zhao, Y. (2019). Bayesian jackknife empirical likelihood. Biometrika, 106, 981-988. · Zbl 1435.62378 |
[36] |
Ciuperca, G., & Salloum, Z. (2016). Empirical likelihood test for high‐dimensional two‐sample model. Journal of Statistical Planning and Inference, 178, 37-60. · Zbl 1346.62026 |
[37] |
Claeskens, G., Jing, B.‐Y., Peng, L., & Zhou, W. (2003). Empirical likelihood confidence regions for comparison distributions and ROC curves. The Canadian Journal of Statistics, 31, 173-190. · Zbl 1039.62038 |
[38] |
Cui, X., Li, R., Yang, G., & Zhou, W. (2020). Empirical likelihood test for a large‐dimensional mean vector. Biometrika, 107, 591-607. · Zbl 1451.62062 |
[39] |
Dai, B., Nachum, O., Chow, Y., Li, L., Szepesvari, C., & Schuurmans, D. (2020). Coindice: Off‐policy confidence interval estimation. In Advances in neural information processing systems (Vol. 33, pp. 9398-9411). Curran Associates, Inc. |
[40] |
Defor, E., & Zhao, Y. (2022). Empirical likelihood inference for the mean past lifetime function. Statistics, 56, 329-346. · Zbl 1493.62234 |
[41] |
DiCiccio, T., Hall, P., & Romano, J. (1991). Empirical likelihood is Bartlett‐correctable. The Annals of Statistics, 19, 1053-1061. · Zbl 0725.62042 |
[42] |
Ding, L., Liu, Z., Li, Y., Liao, S., Liu, Y., Yang, P., Yu, G., Shao, L., & Gao, X. (2019). Linear kernel tests via empirical likelihood for high‐dimensional data. Proceedings of the AAAI Conference on Artificial Intelligence, 33, 3454-3461. |
[43] |
Emerson, S. C., & Owen, A. B. (2009). Calibration of the empirical likelihood method for a vector mean. Electronic Journal of Statistics, 3, 1161-1192. · Zbl 1326.62099 |
[44] |
Fan, G.‐L., Liang, H.‐Y., & Yu, S. (2016). Penalized empirical likelihood for high‐dimensional partially linear varying coefficient model with measurement errors. Journal of Multivariate Analysis, 147, 183-201. · Zbl 1334.62059 |
[45] |
Fan, J., & Lv, J. (2010). A selective overview of variable selection in high dimensional feature space. Statistica Sinica, 20, 101-148. · Zbl 1180.62080 |
[46] |
Feng, H., & Peng, L. (2012a). Jackknife empirical likelihood tests for distribution functions. Journal of Statistical Planning and Inference, 142, 1571-1585. · Zbl 1242.62032 |
[47] |
Feng, H., & Peng, L. (2012b). Jackknife empirical likelihood tests for error distributions in regression models. Journal of Multivariate Analysis, 112, 63-75. · Zbl 1273.62039 |
[48] |
Gamage, R. D. P., & Ning, W. (2020). Inference for long‐memory time series models based on modified empirical likelihood. Austrian Journal of Statistics, 49, 68-79. |
[49] |
Gong, Y., Peng, L., & Qi, Y. (2010). Smoothed jackknife empirical likelihood method for ROC curve. Journal of Multivariate Analysis, 101, 1520-1531. · Zbl 1186.62053 |
[50] |
Guo, H., Zou, C., Wang, Z., & Chen, B. (2014). Empirical likelihood for high‐dimensional linear regression models. Metrika, 77, 921-945. · Zbl 1305.62143 |
[51] |
Hall, P., & Scala, B. L. (1990). Methodology and algorithms of empirical likelihood. International Statistical Review, 58, 109-127. · Zbl 0716.62003 |
[52] |
He, S., Liang, W., Shen, J., & Yang, G. (2016). Empirical likelihood for right censored lifetime data. Journal of the American Statistical Association, 111, 646-655. |
[53] |
Hjort, N. L., McKeague, I. W., & Keilegom, I. V. (2009). Extending the scope of empirical likelihood. The Annals of Statistics, 37, 1079-1111. · Zbl 1160.62029 |
[54] |
Huang, H., & Zhao, Y. (2018). Empirical likelihood for the bivariate survival function under univariate censoring. Journal of Statistical Planning and Inference, 194, 32-46. · Zbl 1392.62295 |
[55] |
Jiang, H., & Zhao, Y. (2022a). Bayesian jackknife empirical likelihood for the error variance in linear regression models. Journal of Statistical Computation and Simulation, in press. · Zbl 07632293 |
[56] |
Jiang, H., & Zhao, Y. (2022b). Transformed jackknife empirical likelihood for probability weighted moments. Journal of Statistical Computation and Simulation, 92, 1618-1639. · Zbl 07546448 |
[57] |
Jiang, Y., Wang, S., Ge, W., & Wang, X. (2011). Depth‐based weighted empirical likelihood and general estimating equations. Journal of Nonparametric Statistics, 23, 1051-1062. · Zbl 1228.62038 |
[58] |
Jing, B.‐Y., Tsao, M., & Zhou, W. (2017). Transforming the empirical likelihood towards better accuracy. The Canadian Journal of Statistics, 45, 340-352. · Zbl 1474.62155 |
[59] |
Jing, B.‐Y., Yuan, J., & Zhou, W. (2009). Jackknife empirical likelihood. Journal of the American Statistical Association, 104, 1224-1232. · Zbl 1388.62136 |
[60] |
Kallus, N., & Uehara, M. (2019). Intrinsically efficient, stable, and bounded off‐policy evaluation for reinforcement learning. In Advances in neural information processing systems (Vol. 32). Curran Associates, Inc. |
[61] |
Karampatziakis, N., Langford, J., & Mineiro, P. (2020). Empirical likelihood for contextual bandits. In 34th conference on neural information processing systems (Vol. 33, pp. 9597-9607). Curran Associates, Inc. |
[62] |
Kitamura, Y. (2007). Empirical likelihood methods in econometrics: Theory and practice. In R.Blundell (ed.), W. K.Newey (ed.), & T.Persson (ed.) (Eds.), Advances in economics and econometrics: Ninth world congress of the econometric society (pp. 174-237). Cambridge University Press. · Zbl 1131.62106 |
[63] |
Lahiri, S. N., & Mukhopadhyay, S. (2012). A penalized empirical likelihood method in high dimensions. The Annals of Statistics, 40, 2511-2540. · Zbl 1373.62132 |
[64] |
Lancaster, T., & Jun, S. J. (2010). Bayesian quantile regression methods. Journal of Applied Econometrics, 25, 287-307. |
[65] |
Lazar, N. A. (2003). Bayesian empirical likelihood. Biometrika, 90, 319-326. · Zbl 1034.62020 |
[66] |
Lazar, N. A. (2021). A review of empirical likelihood. Annual Review of Statistics and its Application, 8, 329-344. |
[67] |
Lazar, N. A., & Mykland, P. A. (1999). Empirical likelihood in the presence of nuisance parameters. Biometrika, 86, 203-211. · Zbl 0917.62029 |
[68] |
Leng, C., & Tang, C. Y. (2012). Penalized empirical likelihood and growing dimensional general estimating equations. Biometrika, 99, 703-716. · Zbl 1437.62522 |
[69] |
Li, G., Lin, L., & Zhu, L. (2012). Empirical likelihood for a varying coefficient partially linear model with diverging number of parameters. Journal of Multivariate Analysis, 105, 85-111. · Zbl 1236.62020 |
[70] |
Li, M., Peng, L., & Qi, Y. (2011). Reduce computation in profile empirical likelihood method. The Canadian Journal of Statistics, 39, 370-384. · Zbl 1271.62072 |
[71] |
Liang, W., & Dai, H. (2021). Empirical likelihood based on synthetic right censored data. Statistics and Probability Letters, 169, 108962. · Zbl 1456.62232 |
[72] |
Liang, W., Dai, H., & He, S. (2019). Mean empirical likelihood. Computational Statistics and Data Analysis, 138, 155-169. · Zbl 1507.62103 |
[73] |
Liang, W., & He, S. (2018). Mean empirical likelihood. Advances in Mathematics (China), 47, 287-295. · Zbl 1413.62058 |
[74] |
Lin, H.‐L., Li, Z., Wang, D., & Zhao, Y. (2017). Jackknife empirical likelihood for the error variance in linear models. Journal of Nonparametric Statistics, 29, 151-166. · Zbl 1369.62060 |
[75] |
Liu, A., & Liang, H. (2017). Jackknife empirical likelihood of error variance in partially linear varying‐coefficient errors‐in‐variables models. Statistical Papers, 58, 95-122. · Zbl 1357.62255 |
[76] |
Liu, X., & Zhao, Y. (2012). Semi‐empirical likelihood inference for the ROC curve with missing data. Journal of Statistical Planning and Inference, 142, 3123-3133. · Zbl 1348.62255 |
[77] |
Liu, Y., & Chen, J. (2010). Adjusted empirical likelihood with high‐order precision. The Annals of Statistics, 38, 1341-1362. · Zbl 1189.62054 |
[78] |
Liu, Y., & Yu, C. W. (2010). Bartlett correctable two‐sample adjusted empirical likelihood. Journal of Multivariate Analysis, 101, 1701-1711. · Zbl 1189.62084 |
[79] |
Liu, Y., Zou, C., & Wang, Z. (2013). Calibration of the empirical likelihood for high‐dimensional data. Annals of the Institute of Statistical Mathematics, 65, 529-550. · Zbl 1396.62105 |
[80] |
Lopez, E. M. M., Keilegom, I. V., & Veraverbeke, N. (2009). Empirical likelihood for non‐smooth criterion functions. Scandinavian Journal of Statistics, 36, 413-432. · Zbl 1194.62069 |
[81] |
Lv, X., Zhang, G., Xu, X., & Li, Q. (2017). Bootstrap‐calibrated empirical likelihood confidence intervals for the difference between two Gini indexes. The Journal of Economic Inequality, 15, 195-216. |
[82] |
Matsushita, Y., & Otsu, T. (2021). Jackknife empirical likelihood: Small bandwidth, sparse network and high‐dimensional asymptotics. Biometrika, 108, 661-674. · Zbl 07459721 |
[83] |
Newey, W. K., & Smith, R. J. (2004). Higher order properties of gmm and generalized empirical likelihood estimators. Econometrica, 72, 219-255. · Zbl 1151.62313 |
[84] |
Nordman, D. J., & Lahiri, S. N. (2014). A review of empirical likelihood methods for time series. Journal of Statistical Planning and Inference, 155, 1-18. · Zbl 1307.62120 |
[85] |
Otsu, T. (2007). Penalized empirical likelihood estimation of semiparametric models. Journal of Multivariate Analysis, 98, 1923-1954. · Zbl 1138.62015 |
[86] |
Owen, A. B. (1988). Empirical likelihood ratio confidence intervals for a single functional. Biometrika, 75, 237-249. · Zbl 0641.62032 |
[87] |
Owen, A. B. (1990). Empirical likelihood ratio confidence regions. The Annals of Statistics, 18, 90-120. · Zbl 0712.62040 |
[88] |
Owen, A. B. (1991). Empirical likelihood for linear models. The Annals of Statistics, 19, 1725-1747. · Zbl 0799.62048 |
[89] |
Owen, A. B. (2001). Empirical likelihood. Chapman and Hall/CRC. · Zbl 0989.62019 |
[90] |
Owen, A. B. (2013). Self‐concordance for empirical likelihood. The Canadian Journal of Statistics, 41, 387-397. · Zbl 1273.62072 |
[91] |
Parente, P. M., & Smith, R. J. (2014). Recent developments in empirical likelihood and related methods. Annual Review of Economics, 6, 77-102. |
[92] |
Peng, L. (2011). Empirical likelihood methods for the Gini index. Australian & New Zealand Journal of Statistics, 53, 131-139. · Zbl 1241.91101 |
[93] |
Peng, L. (2012). Approximate jackknife empirical likelihood method for estimating equations. The Canadian Journal of Statistics, 40, 100-123. · Zbl 1274.62225 |
[94] |
Peng, L., & Qi, Y. (2010). Smoothed jackknife empirical likelihood method for tail copulas. TEST, 19, 514-536. · Zbl 1203.62091 |
[95] |
Peng, L., Qi, Y., & Keilegom, I. V. (2012). Jackknife empirical likelihood method for copulas. TEST, 21, 74-92. · Zbl 1259.62026 |
[96] |
Peng, L., Qi, Y., & Wang, R. (2014). Empirical likelihood test for high dimensional linear models. Statistics and Probability Letters, 86, 85-90. · Zbl 1288.62071 |
[97] |
Priam, R.. (2021). A brief survey of numerical procedures for empirical likelihood. Hal‐03095014. |
[98] |
Qin, G., & Zhao, Y. (2007). Empirical likelihood inference for the mean residual life under random censorship. Statistics and Probability Letters, 77, 549-557. · Zbl 1113.62122 |
[99] |
Qin, G., & Zhou, X.‐H. (2006). Empirical likelihood inference for the area under the ROC curve. Biometrics, 62, 613-622. · Zbl 1097.62099 |
[100] |
Qin, J., & Lawless, J. (1994). Empirical likelihood and general estimating equations. The Annals of Statistics, 22, 300-325. · Zbl 0799.62049 |
[101] |
Qin, Y., Rao, J., & Wu, C. (2010). Empirical likelihood confidence intervals for the Gini measure of income inequality. Economic Modelling, 27, 1429-1435. |
[102] |
Rahman, H., & Zhao, Y. (2022). Empirical likelihood confidence interval for sensitivity to the early disease stage. Pharmaceutical Statistics, 21, 566-583. |
[103] |
Rao, J. N. K., & Wu, C. (2010). Bayesian pseudo‐empirical‐likelihood intervals for complex surveys. Journal of the Royal Statistical Society: Series B, 72, 533-544. · Zbl 1411.62034 |
[104] |
Sang, Y. (2021). A jackknife empirical likelihood approach for testing the homogeneity of K variances. Metrika, 84, 1025-1048. · Zbl 1475.62155 |
[105] |
Sang, Y., Dang, X., & Zhao, Y. (2019). Jackknife empirical likelihood methods for Gini correlations and their equality testing. Journal of Statistical Planning and Inference, 199, 45-59. · Zbl 1418.62221 |
[106] |
Sang, Y., Dang, X., & Zhao, Y. (2020). Depth‐based weighted jackknife empirical likelihood for non‐smooth U‐structure equations. TEST, 29, 573-598. · Zbl 1447.62049 |
[107] |
Sang, Y., Dang, X., & Zhao, Y. (2021). A jackknife empirical likelihood approach for K‐sample tests. The Canadian Journal of Statistics, 49, 1115-1135. · Zbl 1492.62087 |
[108] |
Satter, F., & Zhao, Y. (2020). Nonparametric interval estimation for the mean of a zero‐inflated population. Communications in Statistics—Simulation and Computation, 49, 2059-2067. · Zbl 07552784 |
[109] |
Satter, F., & Zhao, Y. (2021). Jackknife empirical likelihood for the mean difference of two zero‐inflated skewed populations. Journal of Statistical Planning and Inference, 221, 414-422. · Zbl 1455.62096 |
[110] |
Schennach, S. M. (2005). Bayesian exponentially tilted empirical likelihood. Biometrika, 92, 31-46. · Zbl 1068.62035 |
[111] |
Schennach, S. M. (2007). Point estimation with exponentially tilted empirical likelihood. The Annals of Statistics, 35, 634-672. · Zbl 1117.62024 |
[112] |
Sheng, Y., Sun, Y., Huang, C.‐Y., & Kim, M.‐O. (2021). Synthesizing external aggregated information in the penalized Cox regression under population heterogeneity. Statistics in Medicine, 40, 4915-4930. |
[113] |
Sheng, Y., Sun, Y., Huang, C.‐Y., & Kim, M.‐O. (2022). Synthesizing external aggregated information in the presence of population heterogeneity: A penalized empirical likelihood approach. Biometrics, 78(2), 679-690. · Zbl 1520.62323 |
[114] |
Shi, Z. (2016). Econometric estimation with high‐dimensional moment equalities. Journal of Econometrics, 195, 104-119. · Zbl 1443.62506 |
[115] |
Smith, R. J. (1997). Alternative semi‐parametric likelihood approaches to generalised method of moments estimation. The Economic Journal, 107, 503-519. |
[116] |
Sreelakshmi, N., Kattumannil, S. K., & Sen, R. (2021). Jackknife empirical likelihood‐based inference for S‐Gini indices. Communications in Statistics—Simulation and Computation, 50, 1645-1661. · Zbl 1497.62341 |
[117] |
Stewart, P., & Ning, W. (2020a). Confidence intervals for data containing many zeros and ones based on empirical likelihood‐type methods. Journal of Statistical Computation and Simulation, 90, 3376-3399. · Zbl 07481517 |
[118] |
Stewart, P., & Ning, W. (2020b). Modified empirical likelihood‐based confidence intervals for data containing many zero observations. Computational Statistics, 35, 2019-2042. · Zbl 1505.62386 |
[119] |
Sun, Y., Sundaram, R., & Zhao, Y. (2009). Empirical likelihood inference for the Cox model with time‐dependent coefficients via local partial likelihood. Scandinavian Journal of Statistics, 36, 444-462. · Zbl 1198.62138 |
[120] |
Tang, C. Y., & Leng, C. (2010). Penalized high‐dimensional empirical likelihood. Biometrika, 97, 905-919. · Zbl 1204.62050 |
[121] |
Tang, C. Y., & Qin, Y. (2012). An efficient empirical likelihood approach for estimating equations with missing data. Biometrika, 99, 1001-1007. · Zbl 1452.62175 |
[122] |
Tang, C. Y., & Wu, T. T. (2014). Nested coordinate descent algorithms for empirical likelihood. Journal of Statistical Computation and Simulation, 84, 1917-1930. · Zbl 1453.62436 |
[123] |
Tang, X., Li, J., & Lian, H. (2013). Empirical likelihood for partially linear proportional hazards models with growing dimensions. Journal of Multivariate Analysis, 121, 22-32. · Zbl 1328.62569 |
[124] |
Thorne, T. (2015). Empirical likelihood tests for nonparametric detection of differential expression from rna‐seq data. Statistical Applications in Genetics and Molecular Biology, 14, 575-583. · Zbl 1330.92013 |
[125] |
Tsao, M. (2004). Bounds on coverage probabilities of the empirical likelihood ratio confidence regions. The Annals of Statistics, 32, 1215-1221. · Zbl 1091.62040 |
[126] |
Tsao, M. (2013). Extending the empirical likelihood by domain expansion. The Canadian Journal of Statistics, 41, 257-274. · Zbl 1273.62076 |
[127] |
Tsao, M., & Wu, F. (2013). Empirical likelihood on the full parameter space. The Annals of Statistics, 41, 2176-2196. · Zbl 1360.62140 |
[128] |
Tsao, M., & Wu, F. (2014). Extended empirical likelihood for estimating equations. Biometrika, 101, 703-710. · Zbl 1334.62044 |
[129] |
Tsao, M., & Wu, F. (2015). Two‐sample extended empirical likelihood for estimating equations. Journal of Multivariate Analysis, 142, 1-15. · Zbl 1327.62312 |
[130] |
Vexler, A., & Tanajian, H. (2014). Density‐based empirical likelihood procedures for testing symmetry of data distributions and K‐sample comparisons. The Stata Journal, 14, 304-328. |
[131] |
Vexler, A., & Yu, J. (2018). Empirical likelihood methods in biomedicine and health. Chapman and Hall/CRC. |
[132] |
Vexler, A., Yu, J., & Lazar, N. (2017). Bayesian empirical likelihood methods for quantile comparisons. Journal of the Korean Statistical Society, 46, 518-538. · Zbl 1377.62130 |
[133] |
Wang, D., Tian, L., & Zhao, Y. (2017). Smoothed empirical likelihood for the Youden index. Computational Statistics and Data Analysis, 115, 1-10. · Zbl 1466.62209 |
[134] |
Wang, D., Wu, T. T., & Zhao, Y. (2019). Penalized empirical likelihood for the sparse Cox regression model. Journal of Statistical Planning and Inference, 201, 71-85. · Zbl 1421.62083 |
[135] |
Wang, D., & Zhao, Y. (2016). Jackknife empirical likelihood for comparing two Gini indices. The Canadian Journal of Statistics, 44, 102-119. · Zbl 1357.62082 |
[136] |
Wang, L. (2017). Bartlett‐corrected two‐sample adjusted empirical likelihood via resampling. Communications in Statistics—Theory and Methods, 46, 10941-10952. · Zbl 1462.62219 |
[137] |
Wang, L., Chen, J., & Pu, X. (2015). Resampling calibrated adjusted empirical likelihood. The Canadian Journal of Statistics, 43, 42-59. · Zbl 1310.62060 |
[138] |
Wang, L., Li, W., Liu, G., & Pu, X. (2015). Spatial median depth‐based robust adjusted empirical likelihood. Journal of Nonparametric Statistics, 27, 485-502. · Zbl 1328.62222 |
[139] |
Wang, Q.‐H., & Jing, B.‐Y. (2001). Empirical likelihood for a class of functionals of survival distribution with censored data. Annals of the Institute of Statistical Mathematics, 53, 517-527. · Zbl 1009.62092 |
[140] |
Wang, R., & Peng, L. (2011). Jackknife empirical likelihood intervals for Spearman’s rho. North American Actuarial Journal, 15, 475-486. · Zbl 1291.62117 |
[141] |
Wang, R., Peng, L., & Qi, Y. (2013). Jackknife empirical likelihood test for equality of two high dimensional means. Statistica Sinica, 23, 667-690. · Zbl 1379.62041 |
[142] |
Wang, S., Wang, H., Zhao, Y., Cao, G., & Li, Y. (2021). Empirical likelihood ratio tests for varying coefficient geo models. Statistica Sinica, in press. |
[143] |
Wu, C. (2005). Algorithms and R codes for the pseudo empirical likelihood method in survey sampling. Survey Methodology, 31, 239-243. |
[144] |
Wu, F., & Tsao, M. (2014). Two‐sample extended empirical likelihood. Statistics and Probability Letters, 84, 81-87. · Zbl 1407.62159 |
[145] |
Xu, M., & Chen, L. (2018). An empirical likelihood ratio test robust to individual heterogeneity for differential expression analysis of RNA‐seq. Briefings in Bioinformatics, 19, 109-117. |
[146] |
Xue, L. (2009). Empirical likelihood confidence intervals for response mean with data missing at random. Scandinavian Journal of Statistics, 36, 671-685. · Zbl 1223.62055 |
[147] |
Xue, L., & Xue, D. (2011). Empirical likelihood for semiparametric regression model with missing response data. Journal of Multivariate Analysis, 102, 723-740. · Zbl 1327.62231 |
[148] |
Xue, L., & Zhu, L. (2007). Empirical likelihood semiparametric regression analysis for longitudinal data. Biometrika, 94, 921-937. · Zbl 1156.62324 |
[149] |
Xue, L., & Zhu, L. (2012). Empirical likelihood in some nonparametric and semiparametric models. Statistics and Its Interface, 5, 367-378. · Zbl 1383.62093 |
[150] |
Yang, D., & Small, D. S. (2013). An R package and a study of methods for computing empirical likelihood. Journal of Statistical Computation and Simulation, 83, 1363-1372. · Zbl 1431.62011 |
[151] |
Yang, G., Cui, X., & Hou, S. (2017). Empirical likelihood confidence regions in the single‐index model with growing dimensions. Communications in Statistics—Theory and Methods, 46, 7562-7579. · Zbl 1373.62363 |
[152] |
Yang, H., Lu, K., & Zhao, Y. (2017). A nonparametric approach for partial areas under ROC curves and ordinal dominance curves. Statistica Sinica, 27, 357-371. · Zbl 1359.62496 |
[153] |
Yang, H., Yau, C., & Zhao, Y. (2014). Smoothed empirical likelihood inference for the difference of two quantiles with right censoring. Journal of Statistical Planning and Inference, 146, 95-101. · Zbl 1408.62091 |
[154] |
Yang, H., & Zhao, Y. (2012). Smoothed empirical likelihood for ROC curves with censored data. Journal of Multivariate Analysis, 109, 254-263. · Zbl 1241.62036 |
[155] |
Yang, H., & Zhao, Y. (2013). Smoothed jackknife empirical likelihood inference for the difference of ROC curves. Journal of Multivariate Analysis, 115, 270-284. · Zbl 1259.62027 |
[156] |
Yang, H., & Zhao, Y. (2015). Smoothed jackknife empirical likelihood inference for ROC curves with missing data. Journal of Multivariate Analysis, 140, 123-138. · Zbl 1327.62313 |
[157] |
Yang, H., & Zhao, Y. (2017). Smoothed jackknife empirical likelihood for the difference of two quantiles. Annals of the Institute of Statistical Mathematics, 69, 1059-1073. · Zbl 1387.62062 |
[158] |
Yang, H., & Zhao, Y. (2018). Smoothed jackknife empirical likelihood for the one‐sample difference of quantiles. Computational Statistics and Data Analysis, 120, 58-69. · Zbl 1469.62168 |
[159] |
Yang, K., Ding, X., & Yuan, X. (2022). Bayesian empirical likelihood inference and order shrinkage for autoregressive models. Statistical Papers, 63, 97-121. · Zbl 07504785 |
[160] |
Yang, S., & Prentice, R. (2005). Semiparametric analysis of short‐term and long‐term hazard ratios with two‐sample survival data. Biometrika, 92, 1-17. · Zbl 1068.62102 |
[161] |
Yang, Y., & He, X. (2012). Bayesian empirical likelihood for quantile regression. The Annals of Statistics, 40, 1102-1131. · Zbl 1274.62458 |
[162] |
Yiu, A., Goudie, R. J. B., & Tom, B. D. M. (2020). Inference under unequal probability sampling with the Bayesian exponentially tilted empirical likelihood. Biometrika, 107, 857-873. · Zbl 1457.62230 |
[163] |
Yu, X., & Zhao, Y. (2019a). Empirical likelihood inference for semi‐parametric transformation models with length‐biased sampling. Computational Statistics and Data Analysis, 132, 115-125. · Zbl 1507.62200 |
[164] |
Yu, X., & Zhao, Y. (2019b). Jackknife empirical likelihood inference for the accelerated failure time model. TEST, 28, 269-288. · Zbl 1420.62216 |
[165] |
Zang, Y., Zhang, S., Li, Q., & Zhang, Q. (2016). Jackknife empirical likelihood test for high‐dimensional regression coefficients. Computational Statistics and Data Analysis, 94, 302-316. · Zbl 1468.62226 |
[166] |
Zedlewski, J. (2008). Practical empirical likelihood estimation with matElike [Manuscript]. Harvard University. |
[167] |
Zhang, R., Peng, L., & Qi, Y. (2012). Jackknife‐blockwise empirical likelihood methods under dependence. Journal of Multivariate Analysis, 104, 56-72. · Zbl 1352.62053 |
[168] |
Zhang, Y., & Tang, N. (2017). Bayesian empirical likelihood estimation of quantile structural equation models. Journal of Systems Science and Complexity, 30, 122-138. · Zbl 1370.93304 |
[169] |
Zhao, P., Ghosh, M., Rao, J. N. K., & Wu, C. (2020). Bayesian empirical likelihood inference with complex survey data. Journal of the Royal Statistical Society: Series B, 82, 155-174. · Zbl 1440.62403 |
[170] |
Zhao, Y., & Huang, Y. (2007). Test‐based interval estimation under the accelerated failure time model. Communications in Statistics—Simulation and Computation, 36, 593-605. · Zbl 1121.62085 |
[171] |
Zhao, Y., & Jinnah, A. (2012). Inference for Cox’s regression models via adjusted empirical likelihood. Computational Statistics, 27, 1-12. · Zbl 1304.65094 |
[172] |
Zhao, Y., Meng, X., & Yang, H. (2015). Jackknife empirical likelihood inference for the mean absolute deviation. Computational Statistics and Data Analysis, 91, 92-101. · Zbl 1468.62238 |
[173] |
Zhao, Y., Su, Y., & Yang, H. (2020). Jackknife empirical likelihood inference for the Pietra ratio. Computational Statistics and Data Analysis, 152, 1-18. · Zbl 1510.62214 |
[174] |
Zhao, Y., & Yang, S. (2012). Empirical likelihood confidence intervals for regression parameters of the survival rate. Journal of Nonparametric Statistics, 24, 59-70. · Zbl 1416.62629 |
[175] |
Zheng, M., Zhao, Z., & Yu, W. (2012). Empirical likelihood methods based on influence functions. Statistics and its Interface, 5, 355-366. · Zbl 1383.62138 |
[176] |
Zhong, P.‐S., & Chen, S. (2014). Jackknife empirical likelihood inference with regression imputation and survey data. Journal of Multivariate Analysis, 129, 193-205. · Zbl 1360.62148 |
[177] |
Zhong, X., & Ghosh, M. (2016). Higher‐order properties of Bayesian empirical likelihood. Electronic Journal of Statistics, 10, 3011-3044. · Zbl 1358.62037 |
[178] |
Zhou, M. (2015). Empirical likelihood method in survival analysis. Chapman and Hall/CRC. |
[179] |
Zhou, M., & Yang, Y. (2015). A recursive formula for the Kaplan-Meier estimator with mean constraints and its application to empirical likelihood. Computational Statistics, 30, 1097-1109. · Zbl 1329.65038 |
[180] |
Zhou, W., & Jing, B.‐Y. (2003a). Adjusted empirical likelihood method for quantiles. Annals of the Institute of Statistical Mathematics, 55, 689-703. · Zbl 1047.62041 |
[181] |
Zhou, W., & Jing, B.‐Y. (2003b). Smoothed empirical likelihood confidence intervals for the difference of quantiles. Statistica Sinica, 13, 83-95. · Zbl 1017.62030 |
[182] |
Zhu, L., Lin, L., Cui, X., & Li, G. (2010). Bias‐corrected empirical likelihood in a multi‐link semiparametric model. Journal of Multivariate Analysis, 101, 850-868. · Zbl 1181.62039 |
[183] |
Zhu, L., & Xue, L. (2006). Empirical likelihood confidence regions in a partially linear single‐index model. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 68, 549-570. · Zbl 1110.62055 |