PUBLICATIONS

Fernando Andrés Quintana

Books

  1. Müller, P., Quintana, F.A., Jara, A. and Hanson, T. (2015). “Nonparametric Bayesian Data Analysis” Springer Series in Statistics, Springer. (Book's webpage)


Papers, Chapters and Discussions
  1. Müller, Peter and Quintana, Fernando Andrés and Page, Garritt L. “Regression with Variable Dimension Covariates”. To appear in Sankhya A pdf.
  2. Beraha, Mario and Guglielmi, Alessandra and Quintana, Fernando Andrés and de Iorio, Maria and Eriksson, Johan Gunnar and Yap, Fabian. “Childhood Obesity in Singapore: A Bayesian Nonparametric Approach”. To appear in Statistical Modelling pdf.
  3. Pedroso, Ricardo Cunha and Loschi, Rosangela Helena and Quintana, Fernando Andrés (2023)“Multipartition model for multiple change point identification”. Test, 32, 759–783. pdf.
  4. Murua, A. and Quintana, F. A. (2022) “Biclustering via Semiparametric Bayesian Inference”. Bayesian Analysis, 17(3), 969–995. pdf.
  5. Page, G. L. and Quintana, F. A. and Dahl, D. B. (2022) “Dependent Modeling of Temporal Sequences of Random Partitions”. Journal of Computational and Graphical Statistics, 31(2), 614–627. pdf.
  6. Page, G. L. and Quintana, F. A. and Müller, P. (2022) “Clustering and Prediction With Variable Dimension Covariates”. Journal of Computational and Graphical Statistics, 31(2), 466–476. pdf.
  7. Quintana, F. A. and Müller, P. and Jara, A. and MacEachern, S. N. (2022) “The Dependent Dirichlet Process and Related Models”. Statistical Science, 37(1), 24–41. pdf.
  8. Beraha, M. and Guglielmi, A. and Quintana, F.A. (2021) “The semi-hierarchical Dirichlet Process and its application to clustering homogeneous distributions”. Bayesian Analysis, 16(4), 1187–1219. pdf.
  9. Porcu, E. and Bissiri, P. G. and Tagle, F. and Soza, R. and Quintana, F. A. (2021) “Nonparametric Bayesian Modeling and Estimation of Spatial Correlation Functions for Global Data”. Bayesian Analysis, 16(3), 845–873. pdf.

  10. Quinlan, J.J. and Quintana, F. A. and Page, G.L. (2021) “On a class of repulsive mixture models”. Test, 30(2), 445–461. pdf.

  11. Page, G.L. and Quintana, F.A. and Rosner, G.L. (2021) “Discovering Interactions Using Covariate Informed Random Partition Models”. Annals of Applied Statistics, 15(1), 1–21. pdf.
  12. Varas, I. M. and González, J. A. and Quintana, F. A. (2020) “A Bayesian nonparametric latent approach for score distributions in test equating”. Journal of Educational and Behavioral Statistics, 45(6), 639–666. pdf.
  13. Bianchini, I. and Guglielmi, A. and Quintana, F.A. (2020). “Determinantal point process mixtures via spectral density approach”. Bayesian Analysis, 15(1), 187–214. pdf.
  14. Varas, I. and González, J. and Quintana, F.A. (2019). “A New Equating Method Through Latent Variables”, in Quantitative Psychology, Wiberg, M. and Culpepper, S. and Janssen, R. and González, J. and Molenaar, D. (eds), Springer-Verlag, 343–353. pdf.

  15. Pagani-Zanini, C. and Müller, P. and Ji, Y. and Quintana, F.A. (2019), “A Bayesian Random Partition Model for Sequential Refinement and Coagulation”. Biometrics, 75(3), 988–999. pdf.
  16. Quintana, Fernando A. and Loschi, Rosangela H. and Page, Garritt L. (2018), “Bayesian Product Partition Models”, in Wiley StatsRef: Statistics Reference Online, 1–15. pdf.

  17. Quinlan, J.J. and Quintana, F.A. and Page, G.L. (2018) “Density Regression using Repulsive Distributions”. Journal of Statistical Computation and Simulation, 88(15), 2931–2947. pdf.

  18. Page, G.L. and Quintana, F.A. (2018) “Calibrating Covariate Informed Product Partition Models”. Statistics and Computing, 28(5), 1009–1031. pdf.

  19. Guglielmi, A., and Ieva, F., and Paganoni, A.M., and Quintana, F.A. (2018) “A semiparametric Bayesian joint model for multiple mixed-type outcomes: an Application to Acute Myocardial Infarction”. Advances in Data Analysis and Classification, 12(2), 399–423. pdf.

  20. Müller, P. and Quintana, F.A. and Page, G.L. (2018) “Nonparametric Bayesian Inference in Applications”. Statistical Methods & Applications, 27(2), 175–206. pdf.

  21. Barrientos, A. F., and Jara, A., and Quintana, F. A. (2017) “Fully nonparametric regression for bounded data using dependent Bernstein polynomials”. Journal of the American Statistical Association, 112(518), 806–825. pdf.

  22. Murua, A. and Quintana, F. A. (2017). “Semiparametric Bayesian Regression Via Potts Model”. Journal of Computational and Graphical Statistics, 26(2), 265–274. pdf.

  23. Jo, S., and Lee, J., and Müller, P., and Quintana, F. A., and Trippa, L. (2017). “Dependent Species Sampling Models for Spatial Density Estimation”. Bayesian Analysis, 12(2), 379–406. pdf.

  24. Quintana, F. A., and Johnson, W. O. and Waetjen, E. and Gold, E. (2016). “Bayesian Nonparametric Longitudinal Data Analysis”. Journal of the American Statistical Association, 111(515), 1168–1181. pdf.

  25. Nieto-Barajas, L. E. and Quintana, F. A. (2016). “A Bayesian Nonparametric Dynamic AR Model for Multiple Time Series Analysis”. Journal of Time Series Analysis, 37, 675–689. pdf.

  26. Leiva-Yamaguchi, V. and Quintana, F. A. (2016). “A Semiparametric Bayesian Model for Multiple Monotonically Increasing Count Sequences”. Brazilian Journal of Probability and Statistics, 30(2), 155–170. pdf.

  27. Page, G. and Quintana, F. A. (2016). “Spatial Product Partition Models”. Bayesian Analysis 11(1), 265–298. pdf.

  28. Quintana, F. A. and Müller, P., and Papoila, A. L. (2015). “Cluster-specific variable selection for product partition models”. Scandinavian Journal of Statistics, 42(4), 1065–1077. pdf.

  29. Seongil Jo, Jaeyong Lee, Garritt Page, Fernando Quintana, Lorenzo Trippa and Peter Müller (2015). “Spatial Species Sampling and Product Partition Models”. in Nonparametric Bayesian Methods in Biostatistics and Bioinformatics, Mitra, R. and Müller, P. (eds), Springer-Verlag, 359–375.

  30. Barrientos, A. F. and Jara, A. and Quintana, F. A. (2015) “Bayesian density estimation for compositional data using random Bernstein polynomials”. Journal of Statistical Planning and Inference, 166, 116–125. pdf.

  31. Page, G. L., and Quintana, F. A. (2015) “Predictions Based on the Clustering of Heterogeneous Functions via Shape and Subject-Specific Covariates”. Bayesian Analysis, 10(2), 379–410. pdf.

  32. González, J. and Barrientos, A. F. and Quintana, F. A. (2015) “Bayesian Nonparametric Estimation of Test Equating Functions with Covariates”. Computational Statistics & Data Analysis, 89, 222–244. pdf.

  33. González, J. and Barrientos, A. F. and Quintana, F. A. (2015) “A Dependent Bayesian Nonparametric Model for Test Equating”, in Quantitative Psychology Research. Presentations from the 78th Annual Psychometric Society Meeting. Millsap, R.E., Bolt, D.M., van der Ark, L.A., Wang, W.-C. (Eds.) Series: Springer Proceedings in Mathematics & Statistics, Vol. 89, 213–226.

  34. Rodríguez, A., and Quintana, F. A. (2015) “On species sampling sequences induced by residual allocation models”. Journal of Statistical Planning and Inference, 157–158, 108–120. pdf.

  35. Müller, P. and Quintana, F. A. (2014) Discussion on “A Bayesian Nonparametric Modeling Framework for Developmental Toxicity Studies” by Kassandra Fronczyk and Athanasios Kottas. Journal of the American Statistical Association, 109(507), 889–889. pdf.

  36. Müller, P., and Quintana, F. A., and Rosner, G. L., and Maitland, Michael L. (2014) “Bayesian Inference for Longitudinal Data with Nonparametric Treatment Effects”. Biostatistics, 15(2), 341–352. pdf.

  37. Gutiérrez, L., and Quintana, F. A. (2014) “Optimal Information in Authentication of Food and Beverages”. Statistical Modelling International Journal, 14(2), 179–204. pdf.

  38. Jara, A., and Nieto-Barajas, L. and Quintana, F. A. (2013) “A time series model for responses on the unit interval”. Bayesian Analysis, 8(3), 723–740. pdf.

  39. Lee, J., and Quintana, F.A., and Müller, P., and Trippa, L. (2013) “Defining Predictive Probability Functions for Species Sampling Models”. Statistical Science, 28(2), 209–222. pdf.

  40. Di Lucca, M.A., and Guglielmi, A. and Müller, P. and Quintana, F. A. (2013) “A simple class of Bayesian nonparametric autoregression models”. Bayesian Analysis, 8(1), 63–88. pdf.

  41. Ji, Y. and Mitra, R. and Quintana, F. A., and Müller, P. and Jara, A. and Liu, P. and Lu, Y. and Liang, S. (2012) “BM-BC: A Bayesian method of base calling for Solexa sequence data”. BMC Bioinformatics, 13(Suppl 13):S6, 1–9. pdf.

  42. Leon-Novelo, L. and Nebiyou Bekele, B. and Müller, P. and Quintana, F. A. and Wathen, K. (2012) “Borrowing Strength with Non-Exchangeable Priors over Subpopulations”. Biometrics, 68(2), 550–558. pdf.

  43. Barrientos, A.F., and Jara, A., and Quintana, F. A. (2012) “On the support of MacEachern's dependent Dirichlet processes”. Bayesian Analysis, 7(2), 277–310. pdf.

  44. Gutiérrez, L. and Quintana, F. A. (2011) “Multivariate Bayesian Semiparametric Models for Authentication of Food and Beverages”. Annals of Applied Statistics, 5(4), 2385–2402. pdf.

  45. Giardina, F. and Guglielmi, A. and Ruggeri, F. and Quintana, F. A. (2011) “Bayesian First Order Autoregressive Latent Variable Models for Multiple Binary Sequences”. Statistical Modelling International Journal, 11(6), 471–488. pdf.

  46. Griffin, J. and Quintana, F. A. and Steel, M. F. J. (2011) “Flexible and Nonparametric Modelling”, in Handbook of Bayesian Econometrics, J. Geweke, G. Koop and H. Van Dijk (eds.), Oxford University Press, Oxford, pp. 125–182.

  47. Gutiérrez, L. and Quintana, F. A. and von Baer, D. and Mardones, C. (2011) “Multivariate Bayesian Discrimination for Varietal Authentication of Chilean Red Wine”. Journal of Applied Statistics, 38(10), 2099–2109. pdf.

  48. De la Cruz-Mesía, R. and Marshall, G. and Quintana, F. A. (2011) “Logistic regression when covariates are random effects from a non–linear mixed model”. Biometrical Journal, 53(5), 735–749. pdf.

  49. Jara, A. and Hanson, T. and Quintana, F. and Müller, P. and Rosner, G. (2011) “DPpackage: Bayesian Non- and Semi-parametric Modelling in R”. Journal of Statistical Software, 40(5), 1–30. pdf.

  50. Müller, P. and Quintana, F. A. and Rosner, G. L. (2011) “A Product Partition Model with Regression on Covariates”. Journal of Computational and Graphical Statistics, 20(1), 260–278. pdf.

  51. Navarrete, C. and Quintana, F. A. (2011) “Similarity Analysis in Bayesian Random Partition Models”. Computational Statistics & Data Analysis, 55(1) 97–109. pdf.

  52. Jara, A. and Lesaffre, E. and De Iorio, M. and Quintana, F. A. (2010). “Bayesian Semiparametric Inference for Multivariate Doubly-Interval-Censored Data”. Annals of Applied Statistics, 4(4), 2126–2149. pdf. Here is a supplementary material file.

  53. Quintana, F. A. (2010). “Linear Regression with a Dependent Skewed Dirichlet Process”. Chilean Journal of Statistics, 1(2), 35–49. pdf.

  54. Müller, P. and Quintana, F. A. (2010). “More Nonparametric Bayesian Models for Biostatistics”, in Bayesian Nonparametrics, Hjort, N., Holmes, C., Müller, P., and Walker, S. (eds.), Cambridge University Press, Cambridge, pp. 277–294. pdf.

  55. Müller, P. and Quintana, F. A. (2010) “Random Partition Models with Regression on Covariates”. Journal of Statistical Planning and Inference, 140(10), 2801–2808. pdf.

  56. Quintana, F. A. and Müller (2009). Discussion on “Hierarchical Bayesian Modeling of Hitting Performance in Baseball”, by Shane T. Jensen, Blakeley B. McShane and Abraham J. Wyner, Bayesian Analysis, 4(4), 665–668. pdf.

  57. Quintana, F. A. and Steel, M.F.J. and Ferreira, J.T.A.S. (2009). “Flexible Univariate Continuous Distributions”. Bayesian Analysis, 4(3), 497–522. pdf.

  58. Marshall, G. and De la Cruz-Mesía, R. and Quintana, F. A. and Barón A. E. (2009). “Discriminant Analysis for Longitudinal Data with Multiple Continuous Responses and Possibly Missing Data”. Biometrics, 65(1), 69–80. pdf.

  59. Elal-Olivero, D. and Gómez, H.W. and Quintana, F. A. (2009). “Bayesian Modeling Using a Class of Bimodal Skew-Elliptical Distributions”. Journal of Statistical Planning and Inference, 139(4), 1484–1492. pdf.

  60. Iglesias, P. and Orellana, Y. and Quintana, F. (2009). “Nonparametric Bayesian Modeling Using Skewed Dirichlet Process”. Journal of Statistical Planning and Inference, 139(3), 1203–1214. pdf.

  61. Quintana, F. and Müller, P. and Rosner, G. and Relling, M.V. (2008). “A semiparametric Bayesian model for repeatedly repeated binary measurements”. Applied Statistics (Journal of the Royal Statistical Society, Series C), 57(4), 419–431. pdf.

  62. Jara, A., Quintana, F. A., and San Martín, E. (2008) “Linear mixed models with skew-elliptical distributions: A Bayesian approach”. Computational Statistics & Data Analysis. 52(11), 5033–5045. pdf.

  63. Quintana, F. A. and Müller, P., Rosner, G. L., and Munsell, M. (2008). “Semi-parametric Bayesian Inference for Multi-Season Baseball Data”. Bayesian Analysis, 3(2), 317–338. pdf.

  64. Navarrete, C. and Quintana, F. A., and Müller, P. (2008). “Some Issues on Nonparametric Bayesian Modeling Using Species Sampling Models”. Statistical Modelling International Journal, 8(1), 3–21. pdf.

  65. De la Cruz-Mesía, R. and Quintana, F. A. and Marshall, G. (2008) “Model Based Clustering for Longitudinal Data”. Computational Statistics & Data Analysis, 52(3), 1441–1457. pdf.

  66. Newton, M.A. and Quintana, F. A. and den Boon, J.A. and Sengupta, S. and Ahlquist, P. (2007). “Random-set methods identify distinct aspects of the enrichment signal in gene-set analysis”. The Annals of Applied Statistics, 1(1), 85–106. Also as UW Madison Statistics Department Technical Report #1130. pdf.

  67. Müller, P. and Quintana, F. and Rosner, G. (2007) “Semiparametric Bayesian Inference for Multilevel Repeated Measurement Data”. Biometrics, 63(1), 280–289. pdf.

  68. de la Cruz, R. and Quintana, F. (2007) “A model-based approach to Bayesian classification with applications to predicting pregnancy outcomes from longitudinal $\beta$-hCG profiles”. Biostatistics, 8 (2), 228–238. pdf

  69. Gómez, H. and Quintana, F. and Torres, F. (2007) “A New Family of Slash-Distributions with Elliptical Contours”. Statistics and Probability Letters 77 (7), 717–725. pdf.

  70. de la Cruz, R. and Quintana, F. A. and Müller, P. (2007) “Semiparametric Bayesian Classification with Longitudinal Markers”. Applied Statistics (Journal of the Royal Statistical Society, Series C), 56 (2), 119–137. pdf.

  71. Quintana, F. and Silva, A. (2006) “Testing for Differences Among Discrete Distributions: An Application of Model-Based Clustering”. Brazilian Journal of Probability and Statistics, 20, 141–152. pdf.

  72. Quintana, F. (2006). “A predictive view of Bayesian clustering”. Journal of Statistical Planning and Inference, 136(9), 2407–2429. pdf.

  73. Bolfarine, H., Iglesias, P. and Quintana, F. (2005). “Bayesian Identification of Outliers and Change-Points in Measurement Error Models”. Advances in Complex Systems, 8 (4), 433–449. pdf.

  74. Müller, P. and Kottas, A. and Quintana, F. (2005). “Nonparametric Bayesian modeling for multivariate ordinal data”. Journal of Computational and Graphical Statistics, 14 (3), 610–625. pdf.

  75. Quintana, F. and Iglesias, P. and Galea, M. (2005). “Bayesian Robust Estimation of Systematic Risk Using Product Partition Models in the Chilean Stock Markets”. Applied Financial Economic Letters, 1(5), 313–320. pdf.

  76. Gómez, H. and Arellano-Valle, R. and Quintana, F. (2005). “Statistical Inference for A General Class of Asymmetric Univariate Distributions”. Journal of Statistical Planning and Inference, 128 (2), 427–443. pdf.

  77. Iglesias, P. and Orellana, Y. and Quintana, F. (2004). “Nonparametric Bayesian Modeling Using Skewed Dirichlet Process” Proceedings of the Joint Statistical Meetings, Toronto, Canada, August 8-12, 92–96.

  78. Müller, P. and Quintana, F. A. (2004). “Nonparametric Bayesian Data Analysis”. Statistical Science, 19(1), 95–110. pdf.

  79. Müller, P., Quintana, F. and Rosner, G. (2004). “A method for combining inference across related nonparametric Bayesian models.” Journal of the Royal Statistical Society, Series B, 66(3), 735–749. Also as Technical Report PUC/FM-99/6. pdf.

  80. Arellano-Valle, R. and Gómez, H. and Quintana, F. (2004). “A New Class of Skew-Normal Distributions”. Communications in Statistics, Series A, 33(7), 1465–1480. pdf.

  81. Quintana, F. and Müller, P. (2004). “Optimal Sampling for Repeated Binary Measurements”. Canadian Journal of Statistics, 32(1), 73–84. pdf.

  82. Quintana, F. and Müller, P. (2004). “Nonparametric Bayesian Assessment of the Order of Dependence for Binary Sequences”. Journal of Computational and Graphical Statistics, 13 (1), 213–231. Also as Technical Report PUC/FM-06/2001. pdf.

  83. Magnussen, S., Quintana, F. A., Nealis, V. and Hopkin, A. A. (2003). “Testing for Temporal Dependence of Pollen Cone Production in Jack Pine (Pinus banksiana Lamb.)” in Modelling Forest Systems, Amaro, A., Reed, D. and Soares, P. (eds.), San Diego Technical Books, San Diego, pp. 123–130.

  84. Kottas, A., and Müller, P. and Quintana, F. (2003). “A Nonparametric Bayesian Model for Multivariate Ordinal Data” in Proceedings of the Joint Statistical Meetings, San Francisco, California, August 3-7, 2253–2257.

  85. Quintana, F. A. and Iglesias, P.L. (2003). “Bayesian Clustering and Product Partition Models”. Also as Technical Report PUC/FM-06/2000. Journal of the Royal Statistical Society Series B, 65(2), 557–574. pdf.

  86. Iglesias, P.L. and Quintana, F. A. (2003). Discussion on “Bayesian Clustering with Variable and Transformation Selections” by Jun S. Liu, Junni L. Zhang, Michael J. Palumbo and Charles E. Lawrence. In Bayesian Statistics 7, Proceedings of the Seventh Valencia International Meeting. Bernardo, J.M., Bayarri, M.J. Berger, J.O., Dawid, A.P., Heckerman, D., Smith, A.F.M., and West. M. (eds), Oxford Univ. Press, New York, pp. 249–275.

  87. San Martín, E. and Quintana, F. (2002). “ Consistency and Identifiability Revisited”. Also as Technical Report PUC/FM-07/2001. Brazilian Journal of Probability and Statistics, 16(1), 99–106. compressed postscript

  88. Quintana, F. A. and Newton, M.A. (2000). “Computational aspects of Nonparametric Bayesian analysis with applications to the modeling of multiple binary sequences”. Also as Technical Report PUC/FM-98/24. Journal of Computational and Graphical Statistics, 9(4), 711–737. pdf.

  89. Quintana, F. A. (2000) Discussion on “SORE Modeling for Clinical Trials: A Bayesian Perspective” by A. Bouckaert and M. Mouchart. Revista de la Sociedad Chilena de Estadística. 16-17, 26–26.

  90. Newton, M.A. and Quintana, F. A. (1999). Discussion on “Bayesian Nonparametric Inference for Random Distributions and Related Functions” by Walker, S.G., Damien, P., Laud, P.W. and Smith, A.F.M. Journal of the Royal Statistical Society, B, 61, 522.

  91. Quintana, F. A. and Newton, M.A. (1999). “Parametric partially exchangeable models for multiple binary sequences”. Also as Technical Report PUC/FM-96/9. Brazilian Journal of Probability and Statistics, 13(1), 55–76. compressed postscript

  92. Iglesias, P.I. and Quintana, F. A. (1999). Discussion on “Old and Recent Results on the Relationship Between Predictive Inference and Statistical Modelling Either in Nonparametric or Parametric form” by E. Regazzini. In Bayesian Statistics 6, Proceedings of the Sixth Valencia International Meeting. Bernardo, J.M., Berger, J.O., Dawid, A.P. and Smith, A.F.M. (eds), 581–582.

  93. Quintana, F. A., Liu, J.S. and del Pino, G.E. (1999). “Monte Carlo EM with Importance Reweighting and its Applications to Random Effects Models”. Also as Technical Report PUC/FM-97/2. Computational Statistics & Data Analysis, 29, 429–444. pdf.

  94. Newton, M. A., Quintana, F. A., and Zhang, Y. (1998). “Nonparametric Bayes Methods Using Predictive Updating”, in Practical Nonparametric and Semiparametric Bayesian Statistics, Dey, D., Müller, P., and Sinha, D. (eds.), Springer-Verlag, New York, pp. 45–61.

  95. Quintana, F. A. (1998). “Nonparametric Bayesian analysis for assessing homogeneity in $k\times l$ contingency tables with fixed right margin totals”. Also as Technical Report PUC/FM-96/7. Journal of the American Statistical Association, 93(443), 1140–1149. pdf.

  96. Quintana, F. and Newton, M.A. (1998). “Assessing the order of dependence for partially exchangeable binary sequences”. Journal of the American Statistical Association, 93(441), 194–202. pdf.

  97. Quintana, F. and Tam, W. (1996). “Bayesian estimation of Beta-binomial models by simulating posterior densities”. Also as Technical Report PUC/FM-96/1. Revista de la Sociedad Chilena de Estadística, 13 (1,2), 43–56. pdf.

  98. Bianco, J.A., Pyzalski, R.W., Pyzalska, D.M., Sebree, L.A., Hegge, J. and Quintana, F. A. (1996). “Blood Flow Distribution in Necrotic versus Nonnecrotic Rabbit Hearts”. General Cardiology, 87, 294-299. pdf.

  99. Tuite M.J., Yandow D.R„ De Smet A.A., Orwin J.F. and Quintana F. A. (1995) “Effect of field of view on MR diagnosis of rotator cuff tears”. Skeletal Radiology, 24(7), 495–498. pdf.

  100. Quintana, F. A. (1994). “Algunos avances recientes en Computación Estadística”. Journal of the Chilean Statistical Society 11 (1,2), 29–62. pdf.

  101. Tuite, M.J., Yandow, D.R., De Smet, A.A., Orwin, J.S. and Quintana, F. A. (1994). “Diagnosis of Partial and Complete Rotator Cuff Tears Using Combined Gradient Echo and Spin Echo Imaging”. Skeletal Radiology, 23, 541–545. pdf.

  102. De Smet, A.A., Norris, M.A., Yandow, D.R., Quintana, F. A., Graf, B.K, and Keene, J.S. (1993). “MR Diagnosis of Meniscal Tears of the Knee: Importance of High Signal in the Meniscus That Extends to the Surface”. American Journal of Radiology, 161, 101–107. pdf.

  103. Martínez, S. and Quintana, F. (1991). “On a test for generalized upper truncated Weibull distributions”. Statistics and Probability Letters, 12(4), 273–279. pdf.

  104. del Pino, G., Quintana, F., and Rodríguez, W. (1991). “Parametrization in Factorial Generalized Linear Models”. Brazilian Journal of Statistics, 5(2), 103–134.


Work submitted to publication and still under Review
  1. Cremaschi, Andrea and Cadonna, Annalisa and Guglielmi, Alessandra and Quintana, Fernando Andrés “A change-point random partition model for large spatio-temporal datasets” pdf.
  2. Paganin, S. and Page, Garritt L. and Quintana, Fernando Andrés, “Informed Random Partition Models with Temporal Dependence” pdf.
  3. Heiner, Matthew J. and Page, Garritt L. and Quintana, Fernando Andrés. “A Projection Approach to Local Regression and Clustering with Variable-Dimension Covariates”. pdf.