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Publications by Harry Joe


Joe H, Cooke RM, Kurowicka D. Regular vines: generation algorithm and number of equivalence classes. In: Kurowicka D, Joe H. Dependence Modeling: Vine Copula Handbook. Singapore: World Scientific; 2011. pp. 219–231. DOI: 10.1142/9789814299886_0010
Hua L, Joe H. Second order regular variation and conditional tail expectation of multiple risks. Insurance Mathematics & Economics. Elsevier Science BV; 2011; 49: 537-546. DOI: 10.1016/j.insmatheco.2011.08.013
Hua L, Joe H. Tail order and intermediate tail dependence of multivariate copulas. Journal of Multivariate Analysis. Elsevier Inc; 2011; 102: 1454-1471. DOI: 10.1016/j.jmva.2011.05.011
Nikoloulopoulos AK, Joe H, Chaganty NR. Weighted scores method for regression models with dependent data. Biostatistics. Oxford Univ Press; 2011; 12: 653-665. DOI: 10.1093/biostatistics/kxr005
Baser ME, Friedman JM, Joe H, Shenton A, Wallace AJ, Ramsden RT, et al. Empirical development of improved diagnostic criteria for neurofibromatosis 2. Genetics in Medicine. Nature Publishing Group; 2011; 13: 576-581. DOI: 10.1097/GIM.0b013e318211faa9
El-Shaarawi AH, Zhu R, Joe H. Modelling species abundance using the Poisson-Tweedie family. Environmetrics. Wiley-Blackwell; 2011; 22: 152-164. DOI: 10.1002/env.1036
Ng CT, Joe H, Karlis D, Liu J. Composite likelihood for time series models with a latent autoregressive process. Statistica Sinica [Internet]. {Statistica Sinica, TAIWAN; 2011; 21: 279-305. URL: http://www3.stat.sinica.edu.tw/statistica/j21n1/J21N112/J21N112.html
Kurowicka D, Joe H. Dependence Modeling: Vine Copula Handbook [Internet]. Singapore: World Scientific; 2011. DOI: 10.1142/9789814299886 URL: http://www.worldscibooks.com/economics/7699.html


Joe H, Maydeu-Olivares A. A general family of limited information goodness-of-fit statistics for multinomial data [Internet]. Kurowicka D, Joe H. Dependence Modeling: Vine Copula Handbook. Singapore: Springer; 2010. pp. 393-419. DOI: 10.1007/s11336-010-9165-5 URL: {http://www.worldscibooks.com/economics/7699.html doi = 10.1142/9789814299886, @InCollectionCooke.Joe.ea2011
Ng CT, Joe H. Generating random AR(p) and MA(q) Toeplitz correlation matrices. Journal of Multivariate Analysis. Elsevier Inc; 2010; 101: 1532-1545. DOI: 10.1016/j.jmva.2010.01.013
Zhu R, Joe H. Negative binomial time series models based on expectation thinning operators. Journal of Statistical Planning and Inference. Elsevier Science BV; 2010; 140: 1874-1888. DOI: 10.1016/j.jspi.2010.01.031
Joe H, Li H, Nikoloulopoulos AK. Tail dependence functions and vine copulas. Journal of Multivariate Analysis. Elsevier Inc; 2010; 101: 252-270. DOI: 10.1016/j.jmva.2009.08.002
Zhu R, Joe H. Count data time series models based on expectation thinning. Stochastic Models. Taylor & Francis Inc; 2010; 26: PII 925211404. DOI: 10.1080/15326349.2010.498318


Lewandowski D, Kurowicka D, Joe H. Generating random correlation matrices based on vines and extended onion method. Journal of Multivariate Analysis. Elsevier Inc; 2009; 100: 1989-2001. DOI: 10.1016/j.jmva.2009.04.008
Zhu R, Joe H. Modelling heavy-tailed count data using a generalised Poisson-inverse Gaussian family. Statistics & Probability Letters. Elsevier Science BV; 2009; 79: 1695-1703. DOI: 10.1016/j.spl.2009.04.011
Nikoloulopoulos AK, Joe H, Li H. Extreme value properties of multivariate t copulas. Extremes. Springer; 2009; 12: 129-148. DOI: 10.1007/s10687-008-0072-4
Joe H, Lee Y. On weighting of bivariate margins in pairwise likelihood. Journal of Multivariate Analysis. Elsevier Inc; 2009; 100: 670-685. DOI: 10.1016/j.jmva.2008.07.004
Willems G, Joe H, Zamar R. Diagnosing multivariate outliers detected by robust estimators. Journal of Computational and Graphical Statistics. Amer Statistical Assoc; 2009; 18: 73-91. DOI: 10.1198/jcgs.2009.0005


Joe H. Accuracy of Laplace approximation for discrete response mixed models. Computational Statistics & Data Analysis. Elsevier Science BV; 2008; 52: 5066-5074. DOI: 10.1016/j.csda.2008.05.002
Zhao Y, Joe H. Inferences for odds ratio with dependent pairs. Test. Springer; 2008; 17: 101-119. DOI: 10.1007/s11749-006-0025-7
Maydeu-Olivares A, Joe H. An overview of limited information goodness-of-fit testing in multidimensional contingency tables. In: Shigemasu K, Okada A, Imaizumi T, Hoshino T. New Trends in Psychometrics. Universal Academy Press Tokyo, Japan; 2008. pp. 253–262.


Alwan S, Armstrong L, Joe H, Birch PH, Szudek J, Friedman JM. Associations of osseous abnormalities in neurofibromatosis 1. American Journal of Medical Genetics part A. 2007; 143A: 1326-1333. DOI: 10.1002/ajmg.a.31754


Maydeu-Olivares A, Joe H. Limited information goodness-of-fit testing in multidimensional contingency tables. Psychometrika. Springer; 2006; 71: 713-732. DOI: 10.1007/s11336-005-1295-9
Joe H. Generating random correlation matrices based on partial correlations. Journal of Multivariate Analysis. Elsevier Inc; 2006; 97: 2177-2189. DOI: 10.1016/j.jmva.2005.05.010
Qiu W, Joe H. Generation of random clusters with specified degree of separation. Journal of Classification. Springer; 2006; 23: 315-334. DOI: 10.1007/s00357-006-0018-y
Zhu R, Joe H. Modelling count data time series with Markov processes based on binomial thinning. Journal of Time Series Analysis. Blackwell Publishing; 2006; 27: 725-738. DOI: 10.1111/j.1467-9892.2006.00485.x
Joe H, Maydeu-Olivares A. On the asymptotic distribution of Pearson's $X^2$ in cross-validation samples. Psychometrika. Springer; 2006; 71: 587-592. DOI: 10.1007/s11336-005-1284-z
Joe H. Range of correlation matrices for dependent random variables with given marginal distributions. In: Balakrishnan N, Castillo E, Sarabia JM. Advances in Distribution Theory, Order Statistics, and Inference. Birkhauser Boston; 2006. pp. 125-142. DOI: 10.1007/0-8176-4487-3_8
Qiu W, Joe H. Separation index and partial membership for clustering. Computational Statistics & Data Analysis. 2006; 50: 585-603. DOI: 10.1016/j.csda.2004.09.009


Zhao Y, Joe H. Composite likelihood estimation in multivariate data analysis. Canadian Journal of Statistics –- Revue Canadienne de Statistique. 2005; 33: 335-356. DOI: 10.1002/cjs.5540330303
Maydeu-Olivares A, Joe H. Limited- and full-information estimation and goodness-of-fit testing in $2^n$ contingency tables: A unified framework. Journal of the American Statistical Association. 2005; 100: 1009-1020. DOI: 10.1198/016214504000002069
Baser ME, Kuramoto L, Woods R, Joe H, Friedman JM, Wallace AJ, et al. The location of constitutional neurofibromatosis 2 (NF2) splice site mutations is associated with the severity of NF2. Journal of Medical Genetics. 2005; 42: 540-546. DOI: 10.1136/jmg.2004.029504
Joe H, Latif AHMM. Computations for the familial analysis of binary traits. Computational Statistics. 2005; 20: 439-448. DOI: 10.1007/BF02741307


Chaganty NR, Joe H. Efficiency of generalized estimating equations for binary responses. Journal of the Royal Statistical Society Series B –- Statistical Methodology. 2004; 66: 851-860. DOI: 10.1111/j.1467-9868.2004.05741.x
Baser ME, Kuramoto L, Joe H, Friedman JM, Wallace AJ, Gillespie JE, et al. Genotype-phenotype correlations for nervous system tumors in neurofibromatosis 2: A population-based study. American Journal of Human Genetics. 2004; 75: 231-239. DOI: 10.1086/422700
Palmer C, Szudek J, Joe H, Riccardi VM, Friedman JM. Analysis of neurofibromatosis 1 (NF1) lesions by body segment. American Journal of Medical Genetics Part A. 2004; 125A: 157-161. DOI: 10.1002/ajmg.a.20354


Joe H, Nash JC. Numerical optimization and surface estimation with imprecise function evaluations. Statistics and Computing. 2003; 13: 277-286. DOI: 10.1023/A:1024226918553
Woods R, Friedman JM, Evans DGR, Baser ME, Joe H. Exploring the ``Two-Hit hypothesis'' in NF2: Tests of two-hit and three-hit models of vestibular schwannoma development. Genetic Epidemiology. 2003; 24: 265-272. DOI: 10.1002/gepi.10238


Joe H. Stochastic orderings in random utility models. Mathematical Social Sciences. Natl Sci Fdn; 2002; 43: PII S0165-4896(02)00018-5. DOI: 10.1016/S0165-4896(02)00018-5
Baser ME, Friedman JM, Wallace AJ, Ramsden RT, Joe H, Evans DGR. Evaluation of clinical diagnostic criteria for neurofibromatosis 2. Neurology. Lippincott Williams & Wilkins; 2002; 59: 1759-1765. DOI: 10.1212/01.WNL.0000035638.74084.F4
Baser ME, Friedman JM, Aeschliman D, Joe H, Wallace AJ, Ramsden RT, et al. Predictors of the risk of mortality in neurofibromatosis 2. American Journal of Human Genetics. Amer Soc Human Genet; 2002; 71: 715-723. DOI: 10.1086/342716
Zhao Y, Kumar RA, Baser ME, Evans DGR, Wallace A, Kluwe L, et al. Intrafamilial correlation of clinical manifestations in neurofibromatosis 2 (NF2). Genetic Epidemiology. 2002; 23: 245-259. DOI: 10.1002/gepi.10181
Szudek J, Joe H, Friedman JM. Analysis of intrafamilial phenotypic variation in neurofibromatosis 1 (NF1). Genetic Epidemiology. 2002; 23: 150-164. DOI: 10.1002/gepi.01129


Joe H. Multivariate extreme value distributions and coverage of ranking probabilities. Journal of Mathematical Psychology. 2001; 45: 180-188. DOI: 10.1006/jmps.1999.1294