Previous tech reports are available here.
2020
| Id | Authors | Title |
| 20-01 | J.A. Ordoñez, V.H. Lachos & M.O. Prates | Objective Bayesian Analysis for Spatial Student-t Regression Models |
| 20-02 | C.E. Galarza, T-I. Lin, W-L. Wang & V.H. Lachos | High-Order Moments of Truncated Multivariate Student-t Distribution Based on Recurrence Relations |
| 20-03 | C.S. Ferreira, H. Bolfarine & V.H. Lachos | Linear Mixed Models Based on Skew Scale Mixtures of Normal Distribution |
| 20-04 | S. Kim, M-H. Chen, J.G. Ibrahim, A.K. Shah & J. Lin | Bayesian Flexible Hierarchical Skew Heavy-Tailed Multivariate Meta Regression Models for Individual Patient Data with Applications |
| 20-05 | F.L. Schumacher, L.A. Mattos & V.H. Lachos | Scale Mixture of Skew-Normal Linear Mixed Models with Within-Subject Serial Dependence |
| 20-06 | L. Geng & G. Hu | Bayesian Spatial Homogeneity Pursuit for Survival Data with an Application to the SEER Respiration Cancer Data |
| 20-07 | W. Shi, M-H. Chen, L. Kuo & P.O. Lewis | Bayesian Information and Dissonance |
| 20-08 | A. Halder, S. Mohammed, K. Chen & D.K. Dey | Spatial Risk Estimation in Tweedie Compound Poisson Double Generalized Linear Models |
| 20-09 | K. Usmani, T. O’Connor, X. Shen, P. Marasco, A. Carnicer, D.K. Dey & B. Javidi | Three-Dimensional Polarimetric Integral Imaging in Photon-Starved Conditions: Performance Comparison Between Visible and Long Wave Infrared Imaging |
| 20-10 | X. Li & D.K. Dey | The Zero Inflated Conway Maxwell Poisson Distribution for Analyzing Motor Vehicle Crashes |
| 20-11 | A. Halder, S. Mohammed, K. Chen & D.K. Dey | Spatial Tweedie Exponential Dispersion Models: An Application to Insurance Rate-Making |
| 20-12 | H. Bar | Reproducible Code with Latex Compilers |
| 20-13 | C.E. Galarza, L.A. Matos & V.H. Lachos | Moments of the Doubly Truncated Selection Elliptical Distributions with Emphasis on the Unified Multivariate Skew-t Distribution |
| 20-14 | T.B. Mattos, L.A. Matos & V.H. Lachos | Likelihood-based Inference for Mixed-Effects Models with Censored Response Using Skew-Normal Distribution |
| 20-15 | J.L. Padilla G., C.L.N. Azevedo & V.H. Lachos | Parameter Recovery for a Skew Multidimensional Item Response Model: A Comparison of MCMC Algorithms and Measurement of Some Effects of Interest |
| 20-16 | J. Mu, Q. Liu, L.Kuo & G. Hu | Bayesian Variable Selection for Cox Regression Model with Spatially Varying Coefficients with Applications to Louisiana Respiratory Cancer Data |
| 20-17 | H. Bar & H. Wang | Reproducible Science with Latex |
| 20-18 | D.K. Dey & G. Goh | On Foundation of Statistical Inference by C.R. Rao Relating to Information Inequality |
| 20-19 | G. Hu, Z. Ma & I. Paek | A Nonparametric Bayesian Item Response Modeling Approach for Clustering Items and Individuals Simultaneously |
| 20-20 | C.E. Galarza, L.A. Matos & V.H. Lachos | Likelihood-Based Inference for Multivariate Skew-Normal Censored Responses |
| 20-21 | T.B. Mattos, L.A. Matos & V.H. Lachos | Extending Multivariate-t Semiparametric Mixed Models for Longitudinal Data with Censored Responses and Heavy Tails |
| 20-22 | Q. Qi, L. Kuo, S.M. Resnick & E. Grober | A Bayesian Joint Model of Longitudinal Ordinal Outcome and Time-to-Event Data |
| 20-23 | S. Yin, D.K. Dey, E.A. Valdez, G. Gan & J. Vadiveloo | Skewed Link Regression Models for Imbalanced Binary Response with Applications to Life Insurance |
| 20-24 | F.L. Schumacher, C.S. Ferreira, M.O. Prates, A. Lachos, V.H. Lachos | A Robust Nonlinear Mixed-Effects Model for COVID-19 Deaths Data |
| 20-25 | V.H. Lachos, M.O. Prates & D.K. Dey | Heckman Selection-T Model: Parameter Estimation via the EM-Algorithm |
| 20-26 | C.E. Galarza Morales, V.H. Lachos & M. Bourguignon | A Skew-t Quantile Regression for Censored and Missing Data |
| 20-27 | F.L. Schumacher, D.K. Dey, V.H. Lachos | Approximate Inferences for Nonlinear Mixed Effects Models with Scale Mixtures of Skew-Normal Distributions |
| 20-28 | F. Liu, X. Wang, R. Hancock & M-H. Chen | Bayesian Joint Item Response Model of Multi Method Response Data with Application to Computerized Testing |
| 20-29 | H. Jeong & D.K. Dey | Multi-Peril Frequency Credibility Premium via Shared Random Effects |
| 20-30 | X. Li & D.K. Dey | Estimation of COVID-19 in China using Bayesian Spatial Temporal Models |
| 20-31 | D.M. Galvis, V.H. Lachos & L.M. Castro | Predicting Student’s Dropout: A Zero Inflated Censored Poisson Model |
| 20-32 | V.H. Lachos, M. Galea, C. Zeller, M. Prates | Likelihood Inference-Based for Linear Mixed-Effects Models using the Generalized Hyperbolic Distribution |
| 20-33 | K.S. Conceição, M.G. Andrade, V.H. Lachos & N. Ravishanker | k-Modified Distributions for Count Data |
| 20-34 | K.S. Conceição, M.G. Andrade & N. Ravishanker | Zero-Modified Negative Binomial Distribution: Characterizations and Efficiency |
| 20-35 | M.G. Andrade, K.S. Conceição & N. Ravishanker | A Generalized Zero-Modified Count Model for Time Series using Hamiltonian Monte Carlo Algorithm |
| 20-36 | M.G. Andrade, J.A. Achcar, K.S. Conceição & N. Ravishanker | Nonlinear Regression Models with AR-ARCH errors: Applications for Time Series of COVID-19 Deaths |
| 20-37 | W. Yuan, M-H. Chen & J. Zhong | Bayesian Design of Superiority Trials: Methods and Applications |
| 20-38 | M.T. Sheikh, M-H. Chen, J.A. Gelfond, W. Sun & J.G. Ibrahim | Bayesian Innovation for Assessing the Importance of Longitudinal Biomarkers in Fitting Competing Risks Survival Data with Partially Masked Causes |