Journal of Statistics: Advances in Theory and Applications[1] M. Aerts, I. Augustyns and P. Janssen, Smoothing sparse
multinomial data using local polynomial fitting, Journal of
Nonparametric Statistics 8(2) (1997), 127-147.
DOI: https://doi.org/10.1080/10485259708832717
[2] A. Agresti, Categorical Data Analysis, John Wiley & Sons, 2018.
[3] S. E. Ahmed, Construction of improved estimators of multinomial
proportions, Communications in Statistics - Theory and Methods 29(5-6)
(2000), 1273-1291.
DOI: https://doi.org/10.1080/03610920008832544
[4] J. H. Albert, Bayesian Methods for Contingency Tables, Encylopedia
of Biostatistics, 2004.
DOI: https://doi.org/10.1002/9781118445112.stat04849
[5] C. M. Bishop, Pattern Recognition and Machine Learning, Springer,
2006.
[6] Y. M. M. Bishop, S. E. Fienberg and P. W. Holland, Discrete
Multivariate Analysis: Theory and Practice, Cambridge, Mass: MIT
Press, 1975.
[7] D. M. Blei, A. Kucukelbir and J. D. McAuliffe, Variational
inference: A review for statisticians, Journal of the American
Statistical Association 112(518) (2017), 859-877.
DOI: https://doi.org/10.1080/01621459.2017.1285773
[8] P. Burman, Smoothing sparse contingency tables, Sankhya: The
Indian Journal of Statistics, Series A 49(1) (1987), 24-36.
[9] A. C. Cameron and P. K. Trivedi, Regression Analysis of Count
Data, Cambridge University Press, 2013.
[10] J. Carifio and R. J. Perla, Ten common misunderstandings,
misconceptions, persistent myths and urban legends about likert scales
and likert response formats and their antidotes, Journal of Social
Sciences 3(3) (2007), 106-116.
DOI: https://doi.org/10.3844/jssp.2007.106.116
[11] R. J. Carroll, D. Ruppert and L. A. Stefanski, Measurement Error
and Misclassification in Statistics and Epidemiology: Impacts and
Bayesian Adjustments, CRC Press, 2006.
[12] J. Dong and J. Simonoff, The construction and properties of
boundary kernels for smoothing sparse multinomials, Journal of
Computational and Graphical Statistics 3(1) (1994), 57-66.
DOI: https://doi.org/10.2307/1390795
[13] C. X. Feng, A comparison of zero-inflated and hurdle models for
modeling zero-inflated count data, Journal of Statistical
Distributions and Applications 8(1) (2021); Article 8.
DOI: https://doi.org/10.1186/s40488-021-00121-4
[14] S. E. Fienberg and P. W. Holland, Simultaneous estimation of
multinomial cell probabilities, Journal of the American Statistical
Association 68(343) (1973), 683-691.
DOI: https://doi.org/10.2307/2284799
[15] P. Hall and D. M. Titterington, On smoothing sparse multinomial
data, Australian Journal of Statistics 29(1) (1987), 19-37.
DOI: https://doi.org/10.1111/j.1467-842X.1987.tb00717.x
[16] J. M. Hilbe, Modeling Count Data, Cambridge University Press,
2014a.
DOI: https://doi.org/10.1017/CBO9781139236065
[17] J. M. Hilbe, Negative Binomial Regression, Cambridge University
Press, 2014b.
[18] D. W. Hosmer Jr, S. Lemeshow and R. X. Sturdivant, Applied
Logistic Regression, John Wiley & Sons, 2013.
DOI: https://doi.org/10.1002/9781118548387
[19] S. Huang, N. Cai, P. P. Pacheco, S. Narrandes, Y. Wang and W. Xu,
Applications of support vector machine (svm) learning in cancer
genomics, Cancer Genomics & Proteomics 15(1) (2018), 41-51.
DOI: https://doi.org/10.21873/cgp.20063
[20] N. L. Johnson and S. Kotz, Continuous Univariate Distributions,
John Wiley & Sons, 1970.
[21] C. Kleiber and A. Zeileis, Applied Econometrics with R, Springer
Science & Business Media, 2008.
DOI: https://doi.org/10.1007/978-0-387-77318-6
[22] D. Lambert, Zero-inflated poisson regression, with an application
to defects in manufacturing, Technometrics 34(1) (1992), 1-14.
DOI: https://doi.org/10.2307/1269547
[23] R. Likert, A technique for the measurement of attitudes, Archives
of Psychology 140(22) (1932), 1-55.
[24] R. J. Little and D. B. Rubin, Statistical analysis with missing
data, John Wiley & Sons, 2019.
DOI: https://doi.org/10.1002/9781119482260
[25] J. S. Long, Regression Models for Categorical and Limited
Dependent Variables, Sage Publications, 1997.
[26] Y. Min and A. Agresti, Random effect models for repeated measures
of zero-inflated count data, Statistical Modelling 5(1) (2005),
1-19.
DOI: https://doi.org/10.1191/1471082X05st084oa
[27] G. Molenberghs and G. Verbeke, Models for Discrete Longitudinal
Data, Springer, 2007.
[28] S. M. Ross, A First Course in Probability, Pearson Education,
2010.
[29] D. B. Rubin, Multiple imputation for nonresponse in surveys, John
Wiley & Sons, 1987.
DOI: https://doi.org/10.1002/9780470316696
[30] J. Sethuraman, A constructive definition of Dirichlet priors,
Statistica Sinica 4(2) (1994), 639-650.
[31] J. S. Simonoff, A penalty function approach to smoothing large
sparse contingency tables, The Annals of Statistics 11(1) (1983),
208-218.
DOI: https://doi.org/10.1214/aos/1176346071
[32] Y. Teh, M. Jordan, M. Beal and D. Blei, Hierarchical Dirichlet
processes, Journal of the American Statistical Association 101(476)
(2006), 1566-1581.
DOI: https://doi.org/10.1198/016214506000000302
[33] R. Tibshirani, Regression shrinkage and selection via the lasso,
Journal of the Royal Statistical Society: Series B (Methodological)
58(1) (1996), 267-288.
DOI: https://doi.org/10.1111/j.2517-6161.1996.tb02080.x
[34] R. E. Walpole, R. H. Myers, S. L. Myers and K. Ye, Probability &
Statistics for Engineers & Scientists, Pearson Education, 2011.
[35] L. Wickramasinghe, A. Leblanc and S. Muthukumarana, Model-based
estimation of baseball batting metrics, Journal of Applied Statistics
48(10) (2020), 1775-1797.
DOI: https://doi.org/10.1080/02664763.2020.1775792
[36] L. Wickramasinghe, A. Leblanc and S. Muthukumarana, Bayesian
inference on sparse multinomial data using smoothed Dirichlet
distribution with an application to covid-19 data, Model Assisted
Statistics and Applications 18(3) (2023), 207-226.
DOI: https://doi.org/10.3233/MAS-221411
[37] L. Wickramasinghe, A. Leblanc and S. Muthukumarana,
Semi-parametric Bayesian estimation of sparse multinomial
probabilities with an application to the modelling of bowling
performance in T20I cricket, Annals of Biostatistics and Biometric
Applications 5(1) (2023), 1-13.
[38] L. Wickramasinghe, A. Leblanc and S. Muthukumarana, Smoothed
Dirichlet distribution, Journal of Statistical Theory and Applications
22(4) (2023), 237-261.
DOI: https://doi.org/10.1007/s44199-023-00062-8
[39] Q. Xie, C. Han, V. Jin and S. Lin, HiCimpute: A Bayesian
hierarchical model for identifying structural zeros and enhancing
single cell Hi-C data, PLOS Computational Biology 18(6) (2022),
1-19.
DOI: https://doi.org/10.1371/journal.pcbi.1010129
