Publication

Publications: (*: corresponding author)

[46] Emura T*, Shih JH, Ha ID, Wilke RA (2019) Comparison of the marginal hazard model and the sub-distribution hazard model for competing risks under an assumed copula, Stat Methods Med Res: doi.org/10.1177/0962280219892295
[45] Michimae H, Matsunami M, Emura T, (2019) Robust ridge regression for estimating the effects of correlated gene expressions on phenotypic traits, Environ Ecol Stat: doi.org/10.1007/s10651-019-00434-3
[44] Emura T*, Matsui S, Chen HY (2019) compound.Cox: univariate feature selection and compound covariate for predicting survival, Comput Methods Programs Biomed 168: 21-37
[43] Lin WC, Emura T, Sun LH (2019) Estimation under copula-based Markov normal mixture models for serially correlated data, Comm Stat - Simu, doi:10.1080/03610918.2019.1652318
[42] Huang XW, Emura T*(2019) Model diagnostic procedures for copula-based Markov chain models for statistical process control, Comm Stat - Simu, doi:10.1080/03610918.2019.1602647
[41] Sun LH*, Lee CS, Emura T (2018) A Bayesian inference for time series via copula-based Markov chain models, Commun Stat-Siml, doi:10.1080/03610918.2018.1529241
[40] Emura T* and Pan CH (2017) Parametric maximum likelihood inference and goodness-of-fit tests for dependently left-truncated data, a copula-based approach, Stat Pap, doi:10.1007/s00362-017-0947-z
[39] Shih JH, Emura T*(2019) Bivariate dependence measures and bivariate competing risks models under the generalized FGM copula, Stat Pap 60(4) 1101-18
[38] Ha ID*, Kim JM, Emura T (2019) Profile likelihood approaches for semiparametric copula and frailty models for clustered survival data, J Applied Stat 46(14) 2553-71
[37] Sofeu C, Emura T, Rondeau V*(2019) One-step validation method for surrogate endpoints in multiple randomized cancer clinical trials with failure-time endpoints, Stat Med 38:2928-42
[36] Shih JH, Chang YT, Konno Y, Emura T*(2019) Estimation of a common mean vector in bivariate meta-analysis under the FGM copula, Statistics 53(3): 673-95
[35] Shih JH, Lee W, Sun LH, Emura T* (2019) Fitting competing risks data to bivariate Pareto models, Commun Stat-Theor 48(5): 1193-220
[34] He Z, Emura T* (2019) Likelihood inference under the COM-Poisson cure model for survival data - computational aspects, J Chinese Stat Assoc 57: 1-42
[33] Emura T*, Nakatochi M, Matsui S, Michimae H, Rondeau V (2018) Personalized dynamic prediction of death according to tumour progression and high-dimensional genetic factors: meta-analysis with a joint model, Stat Methods Med Res 27(9):2842-58
[32] Emura T*, Liao YT (2018) Critical review and comparison of continuity correction methods: the normal approximation to the binomial distribution, Commun Stat-Siml 47(8), 2266-85
[31] Shih JH, Emura T*(2018) Likelihood-based inference for bivariate latent failure time models with competing risks under the generalized FGM copula, Comput Stat 33(3): 1293-23
[30] Michimae H*, Yoshida A, Emura T, et al. (2018) Reconsidering the estimation of costs of phenotypic plasticity using the robust ridge estimator, Ecol Inform 44: 7-20.
[29] Emura T*, Nakatochi M, Murotani K, Rondeau V (2017) A joint frailty-copula model between tumour progression and death for meta-analysis, Stat Methods Med Res 26(6): 2649-66
[28] Yang SP, Emura T*, (2017) A Bayesian approach with generalized ridge estimation for high-dimensional regression and testing, Commun Stat-Simul 46 (8): 6083-105
[27] Emura T*, Hu YH, Konno Y (2017) Asymptotic inference for maximum likelihood estimators under the special exponential family with double-truncation, Stat Pap 58 (3): 877-909
[26] Emura T*, Long TH, Sun LH (2017) R routines for performing estimation and statistical process control under copula-based time series models, Commun Stat-Simul 46 (4): 3067-87
[25] Chen AC, Emura T*(2017) A modified Liu-type estimator with an intercept term under mixture experiments, Commun Stat-Theor 46(13): 6645-67
[24] Emura T*, Michimae H (2017) A copula-based inference to piecewise exponential models under dependent censoring, with application to time to metamorphosis of salamander larvae, Environ Ecol Stat 24(1) 151–73
[23] Emura T, Chen YH* (2016) Gene selection for survival data under dependent censoring, a copula-based approach, Stat Methods Med Res 25(6): 2840–57
[22] Emura T*, Wang W (2016) Semiparametric inference for an accelerated failure time model with dependent truncation, Ann Inst Stat Math 68 (5): 1073–94
[21] Emura T*, Shiu-SK (2016) Estimation and model selection for left-truncated and right-censored lifetime data with application to electric power transformers analysis, Commun Stat-Simul 45 (9): 3171–89
[20] Emura T*, Ho YT (2016) A decision theoretic approach to change point estimation for binomial CUSUM control charts, Sequential Anal 35 (2): 238-53
[19] Hsu TM, Emura T, Fan TH* (2016) Reliability inference for a copula-based series system life test under multiple type-I censoring, IEEE T Reliab 65 (2): 1069-80
[18] Hu YH, Emura T* (2015) Maximum likelihood estimation for a special exponential family under random double-truncation, Computation Stat 30 (4): 1199-229
[17] Emura T*, Murotani K (2015) An algorithm for estimating survival under a copula-based dependent truncation model, TEST 24 (4): 734-51
[16] Emura T*, Konno Y, Michimae H (2015) Statistical inference based on the nonparametric maximum likelihood estimator under double-truncation, Lifetime Data Anal 21 (3): 397-418
[15] Emura T*, Lin YS (2015) A comparison of normal approximation rules for attribute control charts, Qual Reliab Eng Int 31 (No.3): 411–18
[14] Michimae H, Tezuka A, Emura T, Kishida O (2014) Environment-dependent trade-offs and phenotypuc plasticity in metamorphic timing, Evol Ecol Res 16:617-29
[13] Emura T*, Konno Y (2014) Erratum to: Multivariate normal distribution approaches for dependently ttruncated data, Stat Pap 55 (4): 1233-36
[12] Long TH, Emura T* (2014) A control chart using copula-based Markov chain models, J Chinese Stat Assoc 52 (4): 466-96
[11] Emura T*, Kao FS, Michimae H (2014) An improved nonparametric estimator of sub-distribution function for bivariate competing risk models, J Multivar Anal 132: 229-41
[10] Emura T , Chen YH*, Chen HY (2012) Survival prediction based on compound covariate method under Cox proportional hazard models PLoS ONE 7 (10). doi:10.1371/journal.pone.0047627
[9] Emura T, Wang W* (2012) Nonparametric maximum likelihood estimation for dependent truncation data based on copulas, J Multivar Anal 110, 171-88
[8] Michimae H*, Emura T (2012) Correlated evolution of phenotypic plasticity in metamorphic timing, J Evolution Biol 25: 1331-39
[7] Emura T, Konno Y* (2012) A goodness-of-fit tests for parametric models based on dependently truncated data, Compt Stat Data Anal 56: 2237-50
[6] Emura T, Konno Y* (2012) Multivariate normal distribution approaches for dependently ttruncated data, Stat Pap 53 (No.1): 133-49
[5] Emura T, Wang W* & Hung HN (2011) Semi-parametric inference for copula models for dependently truncated data, Stat Sinica 21: 349-67
[4] Wang W*, Emura T (2011) Comments on inference in multivariate Archimedean copula models by Genest et al., TEST 20: 276-80
[3] Emura T, Lin CW, Wang W* (2010) A goodness-of-fit test for Archimedean copula models in the presence of right censoring, Compt Stat Data Anal 54: 3033-43
[2] Emura T, Wang H* (2010) Approximate tolerance limits under the log-location-scale models in the presence of censoring, Technometrics 52(No.3): 313-23
[1] Emura T, Wang W* (2010) Testing quasi-independence for truncation data, J Multivar Anal 101: 223-39

Software (R packages)

[1] Emura T*, Chen HY, Matsui S, Chen YH (2019) compound.Cox: Univariate Feature Selection and Compound Covariate for Predicting Survival, Ver 3.17. Date 2019-06-02 (since 2012-4-16, Ver 1.0)
[2] Emura T* (2019), joint.Cox: Penalized Likelihood Estimation and Dynamic Prediction under the Joint Frailty-Copula Models Between Tumour Progression and Death for Meta-Analysis, Ver 3.3. Date 2019-06-12 (since 2015-2-28, Ver 1.0)
[3] Emura T* (2018), depend.truncation: Statistical Inference for Parametric and Semiparametric Models Based on Dependently Truncated Data. Ver 1.4. Date 2018-02-27 (since 2012-2-21, Var 1.0)
[4] Emura T*, Huang XW, Chen WR, Long TH (2019), Copula.Markov: estimation and statistical process control under copula-based time series models. Ver 2.4. Date 2019-03-25 (since 2015-3-23, Ver 1.0)
[5] Emura T*, Hu YH, Huang CY (2019), double.truncation: Analysis of Doubly-Truncated Data. Ver 1.4. Date 2018-8-1 (since 2018-7-22, Ver 1.0)

Manuscripts in progress(2020/1/3):

[1] Emura T*, Hsu JH, Estimation of the Mann-Whitney effect in the two-sample problem under dependent censoring(major revision, CSDA)
[2] Achim D, Huang CY, Tseng YK, Emura T*, Likelihood-based analysis of doubly-truncated data under the location-scale and AFT model (major revision, Compt Stat)
[3] Emura T*, Wu BH, Michimae H, Meta-analysis of individual patient data with semi-competing risks under the Weibull joint frailty-copula model (major revision, Comput Stat)
[4] Shih JH, Emura T*, Penalized Cox regression with a five-parameter spline model (major revision, Comm Stat-Theor)
[5] Emura T*, Michimae H, Matsui S, Building web applications for personalized risk prediction of death using R packages joint.Cox and Shiny (in preparation)
[6] Huang XW, Chen WR, Emura T*, Likelihood-based inference for a copula-based Markov chain model with binomial time series (submitted, Stat Pap)
[7] Wang YC, Emura T*, A class of multivariate survival models derived from frailty and copula models (submitted, Comm Stat-Theor)
[8] Shih JH, Konno Y, Chang YT, Emura T*, A class of general pretest estimators for the normal means (submitted to Statistics)
[9] Shih JH, Lin TY, Jimichi M, Emura T*, Robust ridge M-estimators with pretest and Stein-rule shrinkage for an intercept term (submitted, JJDS)
[10] Shinohara S*, Michimae H, Emura T, Dynamic lifetime prediction using a Weibull-based bivariate failure time model: a meta-analysis of individual-patient data (submitted to Comm Stat-Simul)
[11] Huang XW, Wang W, Emura T*, A copula-based Markov chain model for serially dependent event times with a dependent terminal event (submitted, CSDA)
[12] Wang YC, Lo S, Fan TH, Wilke RA, Emura T*, Likelihood-based inference for a frailty-copula model based on competing risks failure time data (submitted to QREI)
[13] Sofeu C*, Emura T, Rondeau V, A joint frailty-copula model for meta-analytic validation of failure time surrogate endpoints in clinical trials (submitted to Biometrical J)
[14] Shih JH, Emura T*, On copula correlation ratio and its generalization (in preparation)
[15] Emura T*, Sofeu C, Rondeau V, Kendall’s tau for individual-level surrogacy for failure time endpoints in meta-analysis (in preparation)
[16] Shih JH, Emura T*, Kim JM, Testing copula directional dependence with applications to nonnegative variables (in preparation)
[17] Yen TJ, Emura T, Mixed model ... (in preparation)

Conference papers: (*: corresponding author)

[1] 江村剛志*、松井茂之、Chen HY (2018) 単変量 Cox 回帰にもとづく遺伝子選択と複合共変量による生存期間の予測, 2018年度統計関連学会連合大会, 東京
[2] Shih JH*, Chang YT, Konno Y, Emura T (2018) Maximum likelihood estimation of a common mean vector in the bivariate FGM copula model for meta-analysis, 2018 JJSM (Japanese Joint Statistical Meeting), Tokyo
[3] Emura T*, Shih JH (2019) Programs for semiparametric Cox regression with cubic M-spline, 11th International Conference on MMR2019 Conference Proceedings, Hong Kong
[4] Wang YC, Emura T* (2019) A frailty-copula model for dependent competing risks in reliability theory, 11th International Conference on MMR2019 Conference Proceedings, Hong Kong

Notes written in Chinese
[1] 江村剛志, 中譯：施嘉翰 (2018), 研究成果報告：死亡時間之個人化預測, 自然科學簡訊第三十卷第一期
[2] 江村剛志, 中譯：施嘉翰, 2017 中、日、韓統計學術研討會之本社代表江村剛志老師專訪, 107年統計通訊第29卷（第 2 期）

Technical Report/Other papers

[1] Emura T, Wang J, Katsuyama H (2008) Assessing the Assumption of the Strongly Ignorable Treatment Assignment Under Assumed Causal Models. Technical Reports of Mathematical Sciences, Chiba Univ 24(No. 8).

[2] Emura T, Wang W (2008), “Asymptotic Analysis and Variance Estimation for Testing Quasi-independence under Truncation,” Technical Reports of Mathematical Sciences, Chiba Univ 24 (No 12).

[3] Emura T, Konno Y (2009), “Multivariate Parametric Approaches for Dependently Left-truncated Data” Technical Reports of Mathematical Sciences, Chiba Univ 25 (No. 2).

[4] Emura T, Katsuyama H, Wang J (2013) "Assessing the Treatment Eect on the Causal Models viaParametric Approaches with Applications to the Study of English EducationalEffect in Japan" MPRA Paper No. 43996.

[5] Emura T, Lin YS (2014), “入門統計学講義ノート(Lecture notes on elementary statistics, in Japanese)" (freely available).