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Generating random correlation matrices based on vines and extended onion method

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Cited by:

  1. Vij, Akshay & Krueger, Rico, 2017. "Random taste heterogeneity in discrete choice models: Flexible nonparametric finite mixture distributions," Transportation Research Part B: Methodological, Elsevier, vol. 106(C), pages 76-101.
  2. Inhan Kang & Minjeong Jeon & Ivailo Partchev, 2023. "A Latent Space Diffusion Item Response Theory Model to Explore Conditional Dependence between Responses and Response Times," Psychometrika, Springer;The Psychometric Society, vol. 88(3), pages 830-864, September.
  3. Ameer Dharamshi & Magali Barbieri & Monica Alexander & Celeste Winant, 2025. "Jointly estimating subnational mortality for multiple populations," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 52(3), pages 71-110.
  4. Benjamin Poignard & Jean-David Fermanian, 2016. "Vine-GARCH process: Stationarity and Asymptotic Properties," Working Papers 2016-03, Center for Research in Economics and Statistics.
  5. Davide Delle Monache & Ivan Petrella & Fabrizio Venditti, 2021. "Price Dividend Ratio and Long-Run Stock Returns: A Score-Driven State Space Model," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(4), pages 1054-1065, October.
  6. Medina-Olivares, Victor & Calabrese, Raffaella & Crook, Jonathan & Lindgren, Finn, 2023. "Joint models for longitudinal and discrete survival data in credit scoring," European Journal of Operational Research, Elsevier, vol. 307(3), pages 1457-1473.
  7. Qinshu Lian & Jing Zhang & James S. Hodges & Yong Chen & Haitao Chu, 2023. "Accounting for post‐randomization variables in meta‐analysis: A joint meta‐regression approach," Biometrics, The International Biometric Society, vol. 79(1), pages 358-367, March.
  8. Guowen Huang & Patrick E. Brown & Sze Hang Fu & Hwashin Hyun Shin, 2022. "Daily mortality/morbidity and air quality: Using multivariate time series with seasonally varying covariances," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(1), pages 148-174, January.
  9. Duncan J. Mayer & Robert L. Fischer, 2022. "Can a measurement error perspective improve estimation in neighborhood effects research? A hierarchical Bayesian methodology," Social Science Quarterly, Southwestern Social Science Association, vol. 103(5), pages 1260-1272, September.
  10. Rossetti, Tomás & Daziano, Ricardo A., 2024. "Crowding multipliers on shared transportation in New York City: The effects of COVID-19 and implications for a sustainable future," Transport Policy, Elsevier, vol. 145(C), pages 224-236.
  11. Follett, Lendie & Yu, Cindy, 2019. "Achieving parsimony in Bayesian vector autoregressions with the horseshoe prior," Econometrics and Statistics, Elsevier, vol. 11(C), pages 130-144.
  12. Hansen, Ole-Petter Moe & Legge, Stefan, 2017. "Quantifying Determinants of Immigration Preferences," Economics Working Paper Series 1710, University of St. Gallen, School of Economics and Political Science.
  13. Soyeon Ahn & John M. Abbamonte, 2020. "A new approach for handling missing correlation values for meta‐analytic structural equation modeling: Corboundary R package," Campbell Systematic Reviews, John Wiley & Sons, vol. 16(1), March.
  14. Md. Tuhin Sheikh & Ming-Hui Chen & Jonathan A. Gelfond & Joseph G. Ibrahim, 2022. "A Power Prior Approach for Leveraging External Longitudinal and Competing Risks Survival Data Within the Joint Modeling Framework," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 14(2), pages 318-336, July.
  15. David Kaplan & Jianshen Chen & Sinan Yavuz & Weicong Lyu, 2023. "Bayesian Dynamic Borrowing of Historical Information with Applications to the Analysis of Large-Scale Assessments," Psychometrika, Springer;The Psychometric Society, vol. 88(1), pages 1-30, March.
  16. Stephen R. Martin & Philippe Rast, 2022. "The Reliability Factor: Modeling Individual Reliability with Multiple Items from a Single Assessment," Psychometrika, Springer;The Psychometric Society, vol. 87(4), pages 1318-1342, December.
  17. Christopher Claassen, 2015. "Measuring university quality," Scientometrics, Springer;Akadémiai Kiadó, vol. 104(3), pages 793-807, September.
  18. Batram, Manuel & Bauer, Dietmar, 2019. "On consistency of the MACML approach to discrete choice modelling," Journal of choice modelling, Elsevier, vol. 30(C), pages 1-16.
  19. Phuc H. Nguyen & Amy H. Herring & Stephanie M. Engel, 2024. "Power Analysis of Exposure Mixture Studies Via Monte Carlo Simulations," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 16(2), pages 321-346, July.
  20. Akshay Vij & Rico Krueger, 2018. "Random taste heterogeneity in discrete choice models: Flexible nonparametric finite mixture distributions," Papers 1802.02299, arXiv.org.
  21. Trung Dung Tran & Emmanuel Lesaffre & Geert Verbeke & Joke Duyck, 2021. "Latent Ornstein‐Uhlenbeck models for Bayesian analysis of multivariate longitudinal categorical responses," Biometrics, The International Biometric Society, vol. 77(2), pages 689-701, June.
  22. Michael Siemon, 2018. "Price Synchronicity, Inter-Firm Networks, and Business Groups in the Middle East and North Africa," Working Papers 1267, Economic Research Forum, revised 10 Dec 2018.
  23. Pedro Luis do N. Silva & Fernando Antônio da S. Moura, 2022. "Fitting multivariate multilevel models under informative sampling," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(4), pages 1663-1678, October.
  24. Lu, Rong, 2020. "Application of machine learning to gas flaring," Thesis Commons g6yvq, Center for Open Science.
  25. Hirofumi Michimae & Takeshi Emura, 2022. "Bayesian ridge estimators based on copula-based joint prior distributions for regression coefficients," Computational Statistics, Springer, vol. 37(5), pages 2741-2769, November.
  26. Akinc, Deniz & Vandebroek, Martina, 2018. "Bayesian estimation of mixed logit models: Selecting an appropriate prior for the covariance matrix," Journal of choice modelling, Elsevier, vol. 29(C), pages 133-151.
  27. Tuitman, Jan & Vanduffel, Steven & Yao, Jing, 2020. "Correlation matrices with average constraints," Statistics & Probability Letters, Elsevier, vol. 165(C).
  28. Zhang, Yixiao & Yu, Cindy L. & Li, Haitao, 2022. "Nowcasting GDP Using Dynamic Factor Model with Unknown Number of Factors and Stochastic Volatility: A Bayesian Approach," Econometrics and Statistics, Elsevier, vol. 24(C), pages 75-93.
  29. Gautier Marti & Victor Goubet & Frank Nielsen, 2021. "cCorrGAN: Conditional Correlation GAN for Learning Empirical Conditional Distributions in the Elliptope," Papers 2107.10606, arXiv.org.
  30. Madar, Vered, 2015. "Direct formulation to Cholesky decomposition of a general nonsingular correlation matrix," Statistics & Probability Letters, Elsevier, vol. 103(C), pages 142-147.
  31. Murphy, James, 2020. "Explanatory Item Response Models for Dyadic Data from Multiple Groups," SocArXiv sx9um_v1, Center for Open Science.
  32. Peter F. Craigmile & Peter Guttorp, 2022. "A combined estimate of global temperature," Environmetrics, John Wiley & Sons, Ltd., vol. 33(3), May.
  33. Yarovaya, Larisa & Matkovskyy, Roman & Jalan, Akanksha, 2021. "The effects of a “black swan” event (COVID-19) on herding behavior in cryptocurrency markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 75(C).
  34. Boratynski, Jakub, 2019. "Bayesian Estimation of the Linear Expenditure System," Conference papers 333113, Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project.
  35. Eric Kemp-Benedict, 2024. "Cost share-induced technological change: An analytical classical-evolutionary model," Journal of Evolutionary Economics, Springer, vol. 34(3), pages 515-567, July.
  36. Ryan Dew & Yuhao Fan, 2021. "Correlated Dynamics in Marketing Sensitivities," Papers 2104.11702, arXiv.org, revised May 2024.
  37. Florianne C. J. Verkroost, 2022. "A Bayesian multivariate hierarchical growth curve model to examine cumulative socio‐economic (dis)advantage among childless adults and parents," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(4), pages 2234-2276, October.
  38. Alejandro Plastina & Sergio H. Lence & Ariel Ortiz‐Bobea, 2021. "How weather affects the decomposition of total factor productivity in U.S. agriculture," Agricultural Economics, International Association of Agricultural Economists, vol. 52(2), pages 215-234, March.
  39. Louis Charlot, 2021. "Bayesian hierarchical analysis of a multifaceted program against extreme poverty," Papers 2109.06759, arXiv.org.
  40. Matthias Breuer & Harm H. Schütt, 2023. "Accounting for uncertainty: an application of Bayesian methods to accruals models," Review of Accounting Studies, Springer, vol. 28(2), pages 726-768, June.
  41. Benjamin Poignard & Jean-Davis Fermanian, 2014. "Dynamic Asset Correlations Based on Vines," Working Papers 2014-46, Center for Research in Economics and Statistics.
  42. Zhongwei Zhang & Reinaldo B. Arellano‐Valle & Marc G. Genton & Raphaël Huser, 2023. "Tractable Bayes of skew‐elliptical link models for correlated binary data," Biometrics, The International Biometric Society, vol. 79(3), pages 1788-1800, September.
  43. Rodrigues, Filipe, 2022. "Scaling Bayesian inference of mixed multinomial logit models to large datasets," Transportation Research Part B: Methodological, Elsevier, vol. 158(C), pages 1-17.
  44. Durante Fabrizio & Puccetti Giovanni & Scherer Matthias & Vanduffel Steven, 2017. "The Vine Philosopher: An interview with Roger Cooke," Dependence Modeling, De Gruyter, vol. 5(1), pages 256-267, December.
  45. Tyler H. Matta & James Soland, 2019. "Predicting Time to Reclassification for English Learners: A Joint Modeling Approach," Journal of Educational and Behavioral Statistics, , vol. 44(1), pages 78-102, February.
  46. Dellaportas, Petros & Titsias, Michalis K. & Petrova, Katerina & Plataniotis, Anastasios, 2023. "Scalable inference for a full multivariate stochastic volatility model," Journal of Econometrics, Elsevier, vol. 232(2), pages 501-520.
  47. Peter Tea & Tim B. Swartz, 2023. "The analysis of serve decisions in tennis using Bayesian hierarchical models," Annals of Operations Research, Springer, vol. 325(1), pages 633-648, June.
  48. Stöber, Jakob & Czado, Claudia, 2014. "Regime switches in the dependence structure of multidimensional financial data," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 672-686.
  49. Flórez, Alvaro J. & Molenberghs, Geert & Van der Elst, Wim & Alonso Abad, Ariel, 2022. "An efficient algorithm to assess multivariate surrogate endpoints in a causal inference framework," Computational Statistics & Data Analysis, Elsevier, vol. 172(C).
  50. Rico Krueger & Taha H. Rashidi & Akshay Vij, 2020. "X vs. Y: an analysis of intergenerational differences in transport mode use among young adults," Transportation, Springer, vol. 47(5), pages 2203-2231, October.
  51. Esther Ulitzsch & Steffi Pohl & Lale Khorramdel & Ulf Kroehne & Matthias Davier, 2022. "A Response-Time-Based Latent Response Mixture Model for Identifying and Modeling Careless and Insufficient Effort Responding in Survey Data," Psychometrika, Springer;The Psychometric Society, vol. 87(2), pages 593-619, June.
  52. Vuorre, Matti & Bolger, Niall, 2017. "Within-subject mediation analysis," OSF Preprints s48e2_v1, Center for Open Science.
  53. Falk, Carl F. & Muthukrishna, Michael, 2021. "Parsimony in model selection: tools for assessing fit propensity," LSE Research Online Documents on Economics 110856, London School of Economics and Political Science, LSE Library.
  54. Ryan Ferguson & Andrew Green, 2018. "Deeply Learning Derivatives," Papers 1809.02233, arXiv.org, revised Oct 2018.
  55. William Bednar & Nick Pretnar, 2019. "Home Production with Time to Consume," 2019 Meeting Papers 328, Society for Economic Dynamics.
  56. Laura Kimmey & Michael Anderson & Valerie Cheh & Evelyn Li & Catherine McLaughlin & Linda Barterian & Jay Crosson & Cara Stepanczuk & Lori Timmins & Jiaqi Li & Shannon Heitkamp & Christine Cheu & Tyle, "undated". "Evaluation of the Independence at Home Demonstration: An Examination of the First Four Years," Mathematica Policy Research Reports f92acd5d008b4cbc82f7e940e, Mathematica Policy Research.
  57. Andreea L. Erciulescu & Jean D. Opsomer, 2022. "A model‐based approach to predict employee compensation components," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(5), pages 1503-1520, November.
  58. Giuseppe Brandi & Ruggero Gramatica & Tiziana Di Matteo, 2019. "Unveil stock correlation via a new tensor-based decomposition method," Papers 1911.06126, arXiv.org, revised Apr 2020.
  59. Murphy, James, 2020. "Explanatory Item Response Models for Dyadic Data from Multiple Groups," SocArXiv sx9um, Center for Open Science.
  60. Kang, Seungwoo & Oh, Hee-Seok, 2024. "Forecasting South Korea’s presidential election via multiparty dynamic Bayesian modeling," International Journal of Forecasting, Elsevier, vol. 40(1), pages 124-141.
  61. Steffen Jahn & Daniel Guhl & Ainslee Erhard, 2024. "Substitution Patterns and Price Response for Plant-Based Meat Alternatives," Rationality and Competition Discussion Paper Series 509, CRC TRR 190 Rationality and Competition.
  62. Jan Havlíček & Petr Tureček & Alice Velková, 2021. "One but not two grandmothers increased child survival in poorer families in west Bohemian population, 1708–1834," Behavioral Ecology, International Society for Behavioral Ecology, vol. 32(6), pages 1138-1150.
  63. Pourahmadi, Mohsen & Wang, Xiao, 2015. "Distribution of random correlation matrices: Hyperspherical parameterization of the Cholesky factor," Statistics & Probability Letters, Elsevier, vol. 106(C), pages 5-12.
  64. Vuorre, Matti & Bolger, Niall, 2017. "Within-subject mediation analysis," OSF Preprints s48e2, Center for Open Science.
  65. Andrew Y. Chen & Jack McCoy, 2022. "Missing Values Handling for Machine Learning Portfolios," Papers 2207.13071, arXiv.org, revised Jan 2024.
  66. Cheng, Sheng & Han, Lingyu & Cao, Yan & Jiang, Qisheng & Liang, Ruibin, 2022. "Gold-oil dynamic relationship and the asymmetric role of geopolitical risks: Evidence from Bayesian pdBEKK-GARCH with regime switching," Resources Policy, Elsevier, vol. 78(C).
  67. Gregory Benton & Wesley J. Maddox & Andrew Gordon Wilson, 2022. "Volatility Based Kernels and Moving Average Means for Accurate Forecasting with Gaussian Processes," Papers 2207.06544, arXiv.org.
  68. Arthur Acolin & Ari Decter-Frain & Matt Hall, 2022. "Small-area estimates from consumer trace data," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 47(27), pages 843-882.
  69. Yunier Bello-Cruz & Max L. N. Gonçalves & Nathan Krislock, 2023. "On FISTA with a relative error rule," Computational Optimization and Applications, Springer, vol. 84(2), pages 295-318, March.
  70. Feng, Xiangnan & Lu, Bin & Song, Xinyuan & Ma, Shuang, 2019. "Financial literacy and household finances: A Bayesian two-part latent variable modeling approach," Journal of Empirical Finance, Elsevier, vol. 51(C), pages 119-137.
  71. Kurowicka, Dorota, 2014. "Joint density of correlations in the correlation matrix with chordal sparsity patterns," Journal of Multivariate Analysis, Elsevier, vol. 129(C), pages 160-170.
  72. Wei Jin & Yang Ni & Leah H. Rubin & Amanda B. Spence & Yanxun Xu, 2022. "A Bayesian nonparametric approach for inferring drug combination effects on mental health in people with HIV," Biometrics, The International Biometric Society, vol. 78(3), pages 988-1000, September.
  73. Matthias Kloft & Raphael Hartmann & Andreas Voss & Daniel W. Heck, 2023. "The Dirichlet Dual Response Model: An Item Response Model for Continuous Bounded Interval Responses," Psychometrika, Springer;The Psychometric Society, vol. 88(3), pages 888-916, September.
  74. Brechmann, Eike C. & Joe, Harry, 2014. "Parsimonious parameterization of correlation matrices using truncated vines and factor analysis," Computational Statistics & Data Analysis, Elsevier, vol. 77(C), pages 233-251.
  75. Terrence D. Jorgensen & Aditi M. Bhangale & Yves Rosseel, 2024. "Two-Stage Limited-Information Estimation for Structural Equation Models of Round-Robin Variables," Stats, MDPI, vol. 7(1), pages 1-34, February.
  76. Forrester, Peter J. & Zhang, Jiyuan, 2020. "Parametrising correlation matrices," Journal of Multivariate Analysis, Elsevier, vol. 178(C).
  77. Amir Ardestani-Jaafari & Erick Delage, 2021. "Linearized Robust Counterparts of Two-Stage Robust Optimization Problems with Applications in Operations Management," INFORMS Journal on Computing, INFORMS, vol. 33(3), pages 1138-1161, July.
  78. Krueger, Rico & Rashidi, Taha H. & Vij, Akshay, 2018. "X vs. Y: An Analysis of Intergenerational Differences in Transport Mode Use Among Young Adults," SocArXiv unezy_v1, Center for Open Science.
  79. Juho Kettunen & Lauri Mehtätalo & Eeva‐Stiina Tuittila & Aino Korrensalo & Jarno Vanhatalo, 2024. "Joint species distribution modeling with competition for space," Environmetrics, John Wiley & Sons, Ltd., vol. 35(2), March.
  80. Holmes, Benjamin & McHale, Ian G. & Żychaluk, Kamila, 2024. "Detecting individual preferences and erroneous verdicts in mixed martial arts judging using Bayesian hierarchical models," European Journal of Operational Research, Elsevier, vol. 312(2), pages 733-745.
  81. Krueger, Rico & Rashidi, Taha H. & Vij, Akshay, 2018. "X vs. Y: An Analysis of Intergenerational Differences in Transport Mode Use Among Young Adults," SocArXiv unezy, Center for Open Science.
  82. Pretnar, Nick, 2022. "Measuring Inequality with Consumption Time," MPRA Paper 118168, University Library of Munich, Germany.
  83. Na Shan & Ping-Feng Xu, 2024. "Bayesian Adaptive Lasso for Detecting Item–Trait Relationship and Differential Item Functioning in Multidimensional Item Response Theory Models," Psychometrika, Springer;The Psychometric Society, vol. 89(4), pages 1337-1365, December.
  84. Esther Ulitzsch & Steffi Pohl & Lale Khorramdel & Ulf Kroehne & Matthias von Davier, 2024. "Using Response Times for Joint Modeling of Careless Responding and Attentive Response Styles," Journal of Educational and Behavioral Statistics, , vol. 49(2), pages 173-206, April.
  85. Balog, Dóra & Bátyi, Tamás László & Csóka, Péter & Pintér, Miklós, 2017. "Properties and comparison of risk capital allocation methods," European Journal of Operational Research, Elsevier, vol. 259(2), pages 614-625.
  86. Lu, Rong, 2020. "Application of machine learning to gas flaring," Thesis Commons g6yvq_v1, Center for Open Science.
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