A mixture model-based nonparametric approach to estimating a count distribution
Author
Abstract
Suggested Citation
DOI: 10.1016/j.csda.2016.11.012
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
References listed on IDEAS
- Woo, Mi-Ja & Sriram, T.N., 2007. "Robust estimation of mixture complexity for count data," Computational Statistics & Data Analysis, Elsevier, vol. 51(9), pages 4379-4392, May.
- Piet Groeneboom & Geurt Jongbloed & Jon A. Wellner, 2008. "The Support Reduction Algorithm for Computing Non‐Parametric Function Estimates in Mixture Models," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 35(3), pages 385-399, September.
- Yong Wang, 2007. "On fast computation of the non‐parametric maximum likelihood estimate of a mixing distribution," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 69(2), pages 185-198, April.
- Lawrence Marsh & Kajal Mukhopadhyay, 1999. "Discrete Poisson kernel density estimation-with an application to wildcat coal strikes," Applied Economics Letters, Taylor & Francis Journals, vol. 6(6), pages 393-396.
- Umashanger, T. & Sriram, T.N., 2009. "L2E estimation of mixture complexity for count data," Computational Statistics & Data Analysis, Elsevier, vol. 53(12), pages 4243-4254, October.
- Wang, Yong, 2007. "Minimum disparity computation via the iteratively reweighted least integrated squares algorithms," Computational Statistics & Data Analysis, Elsevier, vol. 51(12), pages 5662-5672, August.
- Zudi Lu & Yer Van Hui & Andy H. Lee, 2003. "Minimum Hellinger Distance Estimation for Finite Mixtures of Poisson Regression Models and Its Applications," Biometrics, The International Biometric Society, vol. 59(4), pages 1016-1026, December.
- SIMAR, Leopold, 1976. "Maximum likelihood estimation of a compound Poisson process," LIDAM Reprints CORE 271, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Karlis, Dimitris & Xekalaki, Evdokia, 1998. "Minimum Hellinger distance estimation for Poisson mixtures," Computational Statistics & Data Analysis, Elsevier, vol. 29(1), pages 81-103, November.
- Xiang, Liming & Yau, Kelvin K.W. & Lee, Andy H., 2012. "The robust estimation method for a finite mixture of Poisson mixed-effect models," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 1994-2005.
- Dankmar Böhning & Valentin Patilea, 2005. "Asymptotic Normality in Mixtures of Power Series Distributions," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 32(1), pages 115-131, March.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Takada, Teruko, 2009. "Simulated minimum Hellinger distance estimation of stochastic volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2390-2403, April.
- Wu, Jingjing & Karunamuni, Rohana J., 2012. "Efficient Hellinger distance estimates for semiparametric models," Journal of Multivariate Analysis, Elsevier, vol. 107(C), pages 1-23.
- Jingjing Wu & Tasnima Abedin & Qiang Zhao, 2023. "Semiparametric modelling of two-component mixtures with stochastic dominance," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 75(1), pages 39-70, February.
- Madeleine Cule & Richard Samworth & Michael Stewart, 2010. "Maximum likelihood estimation of a multi‐dimensional log‐concave density," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 72(5), pages 545-607, November.
- Jingjing Wu & Rohana J. Karunamuni, 2018. "Efficient and robust tests for semiparametric models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 70(4), pages 761-788, August.
- Balabdaoui, Fadoua & Kulagina, Yulia, 2020. "Completely monotone distributions: Mixing, approximation and estimation of number of species," Computational Statistics & Data Analysis, Elsevier, vol. 150(C).
- Tang, Qingguo & Karunamuni, Rohana J., 2013. "Minimum distance estimation in a finite mixture regression model," Journal of Multivariate Analysis, Elsevier, vol. 120(C), pages 185-204.
- Karunamuni, Rohana J. & Wu, Jingjing, 2011. "One-step minimum Hellinger distance estimation," Computational Statistics & Data Analysis, Elsevier, vol. 55(12), pages 3148-3164, December.
- Umashanger, T. & Sriram, T.N., 2009. "L2E estimation of mixture complexity for count data," Computational Statistics & Data Analysis, Elsevier, vol. 53(12), pages 4243-4254, October.
- Tzougas, George & Karlis, Dimitris & Frangos, Nicholas, 2017. "Confidence intervals of the premiums of optimal Bonus Malus Systems," LSE Research Online Documents on Economics 70926, London School of Economics and Political Science, LSE Library.
- Liming Xiang & Kelvin K. W. Yau & Yer Van Hui & Andy H. Lee, 2008. "Minimum Hellinger Distance Estimation for k-Component Poisson Mixture with Random Effects," Biometrics, The International Biometric Society, vol. 64(2), pages 508-518, June.
- Alfò, Marco & Carbonari, Lorenzo & Trovato, Giovanni, 2023.
"On the effects of taxation on growth: an empirical assessment,"
Macroeconomic Dynamics, Cambridge University Press, vol. 27(5), pages 1289-1318, July.
- Marco Alfò & Lorenzo Carbonari & Giovanni Trovato, 2020. "On the Effects of Taxation on Growth: an Empirical Assessment," CEIS Research Paper 480, Tor Vergata University, CEIS, revised 08 May 2020.
- Marco Alfò & Lorenzo Carbonari & Giovanni Trovato, 2022. "On the Effects of Taxation on Growth: an Empirical Assessment," Working Paper series 22-06, Rimini Centre for Economic Analysis.
- Jordan Stoyanov & Gwo Lin, 2011. "Mixtures of power series distributions: identifiability via uniqueness in problems of moments," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 63(2), pages 291-303, April.
- Payandeh Najafabadi Amir T. & MohammadPour Saeed, 2018. "A k-Inflated Negative Binomial Mixture Regression Model: Application to Rate–Making Systems," Asia-Pacific Journal of Risk and Insurance, De Gruyter, vol. 12(2), pages 1-31, July.
- Andersson, Thomas & Brännäs, Kurt, 1991. "Explaining Cross-Country Variation in Nationalization Frequencies," Working Paper Series 319, Research Institute of Industrial Economics.
- repec:jss:jstsof:36:i02 is not listed on IDEAS
- Seungchul Baek & Junyong Park, 2022. "A computationally efficient approach to estimating species richness and rarefaction curve," Computational Statistics, Springer, vol. 37(4), pages 1919-1941, September.
- Derek S. Young & Xi Chen & Dilrukshi C. Hewage & Ricardo Nilo-Poyanco, 2019. "Finite mixture-of-gamma distributions: estimation, inference, and model-based clustering," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 13(4), pages 1053-1082, December.
- Michel Denuit & Claude Lefèvre & Moshe Shaked, 2000. "Stochastic Convexity of the Poisson Mixture Model," Methodology and Computing in Applied Probability, Springer, vol. 2(3), pages 231-254, September.
- Feng, Oliver Y. & Chen, Yining & Han, Qiyang & Carroll, Raymond J & Samworth, Richard J., 2022. "Nonparametric, tuning-free estimation of S-shaped functions," LSE Research Online Documents on Economics 111889, London School of Economics and Political Science, LSE Library.
- Madison Terrell & Qazi Haque & Jamie L. Cross & Firmin Doko Tchatoka, 2023. "Monetary policy shocks and exchange rate dynamics in small open economies," Working Papers No 10/2023, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
More about this item
Keywords
Count data; Nonparametric minimum power divergence estimation; Poisson mixture model; Power divergence family;All these keywords.
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:csdana:v:109:y:2017:i:c:p:34-44. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/csda .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.