Search Results

A Bayesian Approach to Account for Misclassification and Overdispersion in Count Data,
Wenqi Wu, James Stamey and David Kahle, in IJERPH (2015)
Keywords: misclassification; count data; overdispersion

Fast Bayesian estimation of spatial count data models,
Prateek Bansal, Rico Krueger and Daniel J. Graham, in Computational Statistics & Data Analysis (2021)
Keywords: Variational Bayes; Spatial count data; Negative binomial regression; Pólya-Gamma data augmentation; Accident analysis;

Count-data Analysis of physician Emigration from Developing Countries: A Note,
Elsy Thomas kizhakethalackal, Debasri Mukherjee and Eskander Alvi, in Economics Bulletin (2015)
Keywords: Physician-emigration, medical brain drain, health-infrastructure, count data regression

Regression Analysis of Mixed Panel-Count Data with Application to Cancer Studies,
Yimei Li, Liang Zhu, Lei Liu and Leslie L. Robison, in Statistics in Biosciences (2021)
Keywords: Mixed penal-count data, Regression, Cancer studies, Longitudinal studies

Accounting for Achievement in Athens: A Count Data Analysis of National Olympic Performance,
Glen Roberts, from Department of Economics, University of Victoria (2006)
Keywords: Olympics, count data, Poisson model, negative binomial model

Poisson Weighted Ishita Distribution: Model for Analysis of Over-Dispersed Medical Count Data,
Para Bilal Ahmad and Jan Tariq Rashid, in Statistics in Transition New Series (2020)
Keywords: compounding model, coverage probability, simulation, count data, epileptic seizure counts.

Using Count Data Models in Travel Cost Analysis with Aggregate Data,
Daniel Hellerstein, from University Library of Munich, Germany (1991)
Keywords: Boundary Waters Canoe Area, count data, negative binomial, Poisson, travel cost

A Flexible Mixed Model for Clustered Count Data,
Darcy Steeg Morris and Kimberly F. Sellers, in Stats (2022)
Keywords: correlated count data; dispersion; random effects; longitudinal analysis; COM-Poisson distribution; conjugate distribution

Estimation of hurdle models for overdispersed count data,
Helmut Farbmacher, in Stata Journal (2011)
Keywords: ztpnm, count-data analysis, hurdle models, overdispersion, Poisson-lognormal hurdle models

Bayesian Count Data Modeling for Finding Technological Sustainability,
Sunghae Jun, in Sustainability (2018)
Keywords: count data; Bayesian regression; technological sustainability; Poisson probability distribution; patent analysis

Political influence on historical ESA listings by state: a count data analysis,
Bonnie Harllee, Myungsup Kim and Michael Nieswiadomy, in Public Choice (2009)
Keywords: Endangered Species Act listings, League of Conservation Voters’ environmental scores, NatureServe “at-risk” assessment, Count data analysis, U.S. House of Representatives, U.S. Senate, U.S. Fish & Wildlife Service, Q28, Q20, Q29, K32, H41,

OVERDISP: Stata module to detect overdispersion in count-data models using Stata,
Luiz Paulo Fávero and PatrÌcia Belfiore, from Boston College Department of Economics (2018)
Keywords: overdispersion, count-data models

QCOUNT: Stata program to fit quantile regression models for count data,
Alfonso Miranda, from Boston College Department of Economics (2007)
Keywords: quantile regression, count data

Modeling Longitudinal Count Data,
Sarah Mustillo, Lawrence R. Landerman and Kenneth C. Land, in Sociological Methods & Research (2012)
Keywords: Group differences; growth curve models; marginal effects; count data

Comparative Analysis of Count Data Regression Models on Factors Affecting Infant Mortality,
Sibel Selim and Gizem Kilinc, in EKOIST Journal of Econometrics and Statistics (2021)
Keywords: Count Data Regression Models, Infant Mortality, Demographic and Health Survey, Turkey, Syrian Migrants

A Disaggregate Negative Binomial Regression Procedure for Count Data Analysis,
Venkatram Ramaswamy, Eugene W. Anderson and Wayne S. DeSarbo, in Management Science (1994)
Keywords: negative binomial regression, count data, stochastic models, maximum likelihood, E-M algorithm

A counting process approach to the regression analysis of grouped survival data,
Ian W. McKeague, in Stochastic Processes and their Applications (1988)
Keywords: multivariate counting processes martingale methods censoring weighted least squares additive risk models grouped survival data

Semiparametric regression analysis of panel count data allowing for within-subject correlation,
Bin Yao, Lianming Wang and Xin He, in Computational Statistics & Data Analysis (2016)
Keywords: EM algorithm; Gamma frailty; Monotone splines; Panel count data; Poisson process;

Why to use Poisson regression for count data analysis in consumer behavior research,
Feihong Xia, in Journal of Marketing Analytics (2023)
Keywords: Consumer behavior research, Count data, Poisson regression, Hypothesis testing, False negative, False positive

A Bayesian approach for semiparametric regression analysis of panel count data,
Jianhong Wang and Xiaoyan Lin, in Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data (2020)
Keywords: Monotone splines, Nonhomogeneous Poisson process, Panel count data, Proportional mean model, Semiparametric regression

Semiparametric analysis of multivariate panel count data with nonlinear interactions,
Weiwei Wang, Yijun Wang and Xiaobing Zhao, in Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data (2022)
Keywords: Multivariate panel count data, Varying coefficient, Local logarithm partial likelihood function, Taylor expansion

Regression analysis of clustered panel count data with additive mean models,
Weiwei Wang, Zhiyang Cui, Ruijie Chen, Yijun Wang and Xiaobing Zhao, in Statistical Papers (2024)
Keywords: Panel count data, Cluster effect, Additive mean model, Estimating equation, Marginal model.

Modelling and analysis of count data using a renewal process,
M. J. Faddy, in Statistics & Probability Letters (1996)
Keywords: Poisson distribution Renewal process Over-dispersion Under-dispersion Data analysis

A conditional count model for repeated count data and its application to GEE approach,
Rajib Dey and M. Ataharul Islam, in Statistical Papers (2017)
Keywords: Count data, Generalized estimating equations, Conditional probability

Religion and Labor: An Examination of Religious Service Attendance and Unemployment Using Count Data Methods,
Neil Meredith, in Eastern Economic Journal (2017)
Keywords: unemployment, religion, count data

Count data models with variance of unknown form: an application to a hedonic model of worker absenteeism,
Thomas Kniesner, from Universidad Carlos III de Madrid. Departamento de Estadística (1994)
Keywords: Count data models

Modeling female fertility using inflated count data models,
Maria Melkersson and Dan-Olof Rooth, in Journal of Population Economics (2000)
Keywords: Fertility, inflated count data models

Dynamic conditional score patent count panel data models,
Szabolcs Blazsek, from Universidad Carlos III de Madrid. Departamento de Economía (2015)
Keywords: Patent count panel data models

The value of the trout fishery at Rhodes, North Eastern Cape, South Africa: a travel cost analysis using count data models,
Mario du Preez and Stephen Hosking, in Journal of Environmental Planning and Management (2011)
Keywords: trout, South Africa, travel cost method, count data, recreational value,

Properties of estimators of count data model with endogenous switching,
Kosuke Oya, in Mathematics and Computers in Simulation (MATCOM) (2005)
Keywords: Count data; Endogenous switching; Monte Carlo experiment;

COUNT DATA MODELS FOR A CREDIT SCORING SYSTEM,
Montserrat Guillen and Manuel Artís, from Risk and Insurance Archive (1994)
Keywords: count data, NBD models, credit scoring.

COUNT DATA MODELS FOR A CREDIT SCORING SYSTEM,
Montserrat Guillen and Manuel Artís, from University Library of Munich, Germany (1994)
Keywords: count data, NBD models, credit scoring.

Modeling underdispersed count data with generalized Poisson regression,
Tammy Harris, Zhao Yang and James W. Hardin, in Stata Journal (2012)
Keywords: gpoisson, Poisson, count data, overdispersion, underdispersion

Long Memory Conditional Heteroscedasticity in Count Data,
Mawuli Segnon and Manuel Stapper, from Center for Quantitative Economics (CQE), University of Muenster (2019)
Keywords: Count Data, Poisson Autoregression, Fractionally Integrated, INGARCH

Spatial Errors in Count Data Regressions,
Marinho Bertanha and Moser Petra, in Journal of Econometric Methods (2016)
Keywords: citations, count data, patents, Poisson panel models, spatial correlation

Geographically weighted bivariate generalized Poisson regression: application to infant and maternal mortality data,
Purhadi, Sutikno, Sarni Maniar Berliana and Dewi Indra Setiawan, in Letters in Spatial and Resource Sciences (2021)
Keywords: Count data, Spatial analysis, Spatial heterogeneity

Calibration tests for count data,
Wei Wei and Leonhard Held, in TEST: An Official Journal of the Spanish Society of Statistics and Operations Research (2014)
Keywords: Calibration test, Count data, Predictive distribution, Proper scoring rules, 62M20 Prediction,

Association of Vehicle Count Data Obtained Via Image Processing Techniques Compared with Microsimulation Program Analysis Results,
Seyitali İlyas, Bahadır Ersoy Ulusoy, Sevil Köfteci and Yalçın Albayrak, in Networks and Spatial Economics (2024)
Keywords: Signalized intersection analysis, Microsimulation, Traffic management, Vehicle counting, Image processing

Residual Diagnostic Methods for Bell-Type Count Models,
Hatice Tul Kubra Akdur, Duygu Kilic and Hulya Bayrak, in Statistics in Biosciences (2024)
Keywords: Count data, Zero-inflated regression models, Overdispersion, Residual analysis

Modelling and understanding count processes through a Markov-modulated non-homogeneous Poisson process framework,
Benjamin Avanzi, Greg Taylor, Bernard Wong and Alan Xian, in European Journal of Operational Research (2021)
Keywords: Risk analysis; Markov processes; Count processes; Data analysis; EM algorithm;

Penalized Estimation of a Quantile Count Model for Panel Data,
Matthew Harding and Carlos Lamarche, in Annals of Economics and Statistics (2019)
Keywords: Quantile Regression, Penalized Estimation, Count Data, Scanner Data

Empirical Bayesian Selection of Hypothesis Testing Procedures for Analysis of Sequence Count Expression Data,
Pounds Stanley B., Gao Cuilan L. and Zhang Hui, in Statistical Applications in Genetics and Molecular Biology (2012)
Keywords: empirical bayes, multiple testing, mRNA-seq data, differential expression, false discovery rate, sequence count expression data

Bivariate Negative Binomial Generalized Linear Models for Environmental Count Data,
Masakazu Iwasaki and Hiroe Tsubaki, in Journal of Applied Statistics (2006)
Keywords: Bivariate negative binomial generalized linear models (BIVARNB GLM), bivariate negative binomial distribution, bivariate gamma type GLM, bivariate count data analysis,

Modeling heaped count data,
Tammy H. Cummings, James W. Hardin, Alexander C. McLain, James R. Hussey, Kevin J. Bennett and Gina M. Wingood, in Stata Journal (2015)
Keywords: heapcr, ziheapcr, heapr, ziheapr, count data, heaping, Poisson, generalized Poisson, negative binomial, zero-inflation, interval censored, mixture, rescaled

Modeling interregional research collaborations in German biotechnology using industry directory data: A quantitative social network analysis,
Timo Mitze and Falk Strotebeck, from University Library of Munich, Germany (2017)
Keywords: Biotechnology, research collaboration, cluster policy, social network analysis, count data

Measurements of fractal dimension by box-counting: a critical analysis of data scatter,
Stéphane Buczkowski, Patrice Hildgen and Louis Cartilier, in Physica A: Statistical Mechanics and its Applications (1998)
Keywords: Box-counting; Fractal dimension; Multifractal;

Bank Branch Location: a Count Analysis,
Charles Okeahalam, in Spatial Economic Analysis (2009)
Keywords: Bank branches, count analysis, South Africa, C31, N27, R32,

intcount: A command for fitting count-data models from interval data,
Stephen Pudney, in Stata Journal (2019)
Keywords: intcount, count data, interval data, zero-inflated, interpolation, Understanding Society

Repeat tourism in Uruguay: modelling truncated distributions of count data,
Juan Brida, Juan Sebastián Pereira and Raffaele Scuderi, from University Library of Munich, Germany (2012)
Keywords: Repeat tourism; Uruguay; Quantile Regression; Count Data

Estimating the carbon dioxide emission levels of G7 countries: A count data approach,
Siele Jean Tuo, Chang Li, Ettien Fulgence Brou, Diby Francois Kassi and Yobouet Thierry Gnangoin, in Energy & Environment (2024)
Keywords: G7; count data models; energy; carbon emissions

The Determinants of Health Care Utilization in Portugal: An Approach with Count Data Models,
João Cotter Salvado, in Swiss Journal of Economics and Statistics (SJES) (2008)
Keywords: health care utilization; count data models; Portugal

Partial identification in nonseparable count data instrumental variable models,
Dongwoo Kim, in The Econometrics Journal (2020)
Keywords: Count data, instrumental variables, partial identification

Multivariate modelling of time series count data: an autoregressive conditional Poisson model,
Andréas Heinen and Erick Rengifo, from Université catholique de Louvain, Center for Operations Research and Econometrics (CORE) (2003)
Keywords: count data, time series, copula, market microstructure

Repeat tourism in Uruguay: modelling truncated distributions of count data,
Juan Brida, Juan Pereyra and Raffaele Scuderi, in Quality & Quantity: International Journal of Methodology (2014)
Keywords: Repeat tourism, Uruguay, Quantile regression, Count data,

Semiparametric Count Data Modeling with an Application to Health Service Demand,
P. Bach, Helmut Farbmacher and M. Spindler, from HEDG, c/o Department of Economics, University of York (2016)
Keywords: semiparametric; nonparametric; count data; health care demand;

Fertility Assimilation of Immigrants: Evidence from Count Data Models,
Jochen Mayer and Regina Riphahn, from Institute of Labor Economics (IZA) (1999)
Keywords: assimilation, immigrant fertility, Count data estimation, disruption

Estimating Willingness to Pay from Count Data When Survey Responses are Rounded,
Ian B. Page, Erik Lichtenberg and Monica Saavoss, in Environmental & Resource Economics (2020)
Keywords: Coarsened data, Count data, Heaped data, Poisson, Recreation demand, Rounding

A new count data model applied in the analysis of vaccine adverse events and insurance claims,
Dar Showkat Ahmad, Hassan Anwar, Ahmad Peer Bilal and Wani Sameer Ahmad, in Statistics in Transition New Series (2021)
Keywords: poisson distribution, weighted exponential distribution, compound distribution, count data, maximum likelihood estimation.

Joint analysis of panel count data with an informative observation process and a dependent terminal event,
Jie Zhou, Haixiang Zhang, Liuquan Sun and Jianguo Sun, in Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data (2017)
Keywords: Estimating equation, Informative observation process, Joint modeling, Panel count data, Terminal event

Size of economic activity and occurrence of fatal traffic accidents: a count panel data analysis on Fukuoka prefecture in Japan,
Yoshitsugu Kitazawa, from Kyushu Sangyo University, Faculty of Economics (2010)
Keywords: traffic accident, number of fatalities, gross municipal product, count panel data, GMM, diseconomy of scale

A simple and useful regression model for fitting count data,
Marcelo Bourguignon and Rodrigo M. R. Medeiros, in TEST: An Official Journal of the Spanish Society of Statistics and Operations Research (2022)
Keywords: BerG distribution, Count data, Regression models, Overdispersion, Underdispersion

An empirical analysis of the demand for health using the European Community Household Panel,
Sergi Jimenez-Martin, Jose Labeaga and Maite Martinez-Granado, from Universidad Carlos III de Madrid. Departamento de Economía (2000)
Keywords: Count data

Multivariate Sarmanov Count Data Models,
Eugenio Miravete, from C.E.P.R. Discussion Papers (2009)
Keywords: Sarmanov distributions; Double poisson; Gamma; Multivariate count data models; Tariff options

On construction and simulation of count data models,
Per-Erik Hagmark, in Mathematics and Computers in Simulation (MATCOM) (2008)
Keywords: Count data model; Under/over-dispersion; Discretization; Variate generation; Alias method;

Modeling count data with generalized distributions,
Tammy Harris, Joseph Hilbe and James W. Hardin, in Stata Journal (2014)
Keywords: gbin, zigbin, nbregf, nbregw, zinbregf, zinbregw, binomial,Waring, count data, overdispersion, underdispersion

Models for count data with endogenous participation,
William Greene, in Empirical Economics (2009)
Keywords: Poisson regression, Count data, Heterogeneity, Lognormal, Two part model, C14, C23, C25,

‘Adopt a Hypothetical Pup’: A Count Data Approach to the Valuation of Wildlife,
Roberto Martinez-Espineira, in Environmental & Resource Economics (2007)
Keywords: contingent valuation, count data, coyotes, wildlife, willingness to pay, zero-inflated count data models, Q20, Q26,

A reinvestigation of contract duration using Quantile Regression for Counts analysis,
Chunping Liu and Amy (Chen) Peng, in Economics Letters (2010)
Keywords: Contract duration Quantile Regression Count data

Planned Fertility and Family Background: A Quantile Regression for Counts Analysis,
Alfonso Miranda, from Centre for Economic Research, Keele University (2005)
Keywords: Fertility, Family Background, Count Data, Quantile Regression.

Count Regression and Machine Learning Techniques for Zero-Inflated Overdispersed Count Data: Application to Ecological Data,
Bonelwa Sidumo, Energy Sonono and Isaac Takaidza, in Annals of Data Science (2024)
Keywords: Count data, Ecology, Machine learning, Overdispersion, Zero-inflation

On the Turing estimator in capture–recapture count data under the geometric distribution,
Orasa Anan, Dankmar Böhning and Antonello Maruotti, in Metrika: International Journal for Theoretical and Applied Statistics (2019)
Keywords: Capture–recapture data, Geometric distribution, Heterogeneity, Count data, Variance estimation

A Review of Spatiotemporal Models for Count Data in R Packages. A Case Study of COVID-19 Data,
Maria Victoria Ibañez, Marina Martínez-Garcia and Amelia Simó, in Mathematics (2021)
Keywords: COVID-19; count data; spatiotemporal models; R packages

Analyzing health outcomes measured as bounded counts,
John Mullahy, in Journal of Health Economics (2024)
Keywords: Count data; Bounded outcomes;

Zero-Inflated Patent Data Analysis Using Generating Synthetic Samples,
Daiho Uhm and Sunghae Jun, in Future Internet (2022)
Keywords: zero-inflated data; synthetic sample; patent analysis; count data; classification and regression trees

Modeling Repeated Count Data: Some Extensions of the Rasch Poisson Counts Model,
Marijtje A. J. van Duijn and Margo G. H. Jansen, in Journal of Educational and Behavioral Statistics (1995)
Keywords: Poisson distribution; gamma distribution; multinomial distribution; Dirichlet distribution; overdispersion; interaction; repeated count data

Clustering for time-varying relational count data,
Satoshi Goto, Mariko Takagishi and Hiroshi Yadohisa, in Computational Statistics & Data Analysis (2021)
Keywords: Bayesian model; Clustering; Count data; Time-varying relational data; Zero-inflated poisson;

Bayesian inference on quasi-sparse count data,
Jyotishka Datta and David B. Dunson, in Biometrika (2016)
Keywords: Count data, High-dimensional data, Local-global shrinkage, Rare variant, Shrinkage prior, Zero-inflation

Count Data Modelling and Tourism Demand,
Jörgen Hellström, from Umeå University, Department of Economics (2002)
Keywords: Time series; Count data; INARMA; Unit root; Aggregation; Forecasting; Tourism; Truncation; Inflation; Simulated maximum likelihood; Bivariate hurdle model.

Semiparametric partially linear varying coefficient models with panel count data,
Xin He, Xuenan Feng, Xingwei Tong and Xingqiu Zhao, in Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data (2017)
Keywords: Asymptotic normality, B-spline, Counting process, Maximum likelihood, Maximum pseudo-likelihood, Panel count data, Varying-coefficient

Estimating the p-Variation Index of a Sample Function: An Application to Financial Data Set,
Rimas Norvaiša and Donna Mary Salopek, in Methodology and Computing in Applied Probability (2002)
Keywords: estimation, p-variation index, box-counting index, financial data analysis

IRT–ZIP Modeling for Multivariate Zero-Inflated Count Data,
Lijuan Wang, in Journal of Educational and Behavioral Statistics (2010)
Keywords: multivariate zero-inflated count data; IRT–ZIP; item properties

Adopt a hypothetical pup’: A count data approach to the valuation of wildlife,
Roberto Martinez-Espineira, from University Library of Munich, Germany (2004)
Keywords: coyotes, wildlife, contingent valuation, count data, zero- inflation

Adopt a hypothetical pup: A count data approach to the valuation of wildlife,
Roberto Martinez-Espineira, from University Library of Munich, Germany (2004)
Keywords: coyotes, wildlife, contingent valuation, count data, zero- inflation

A hyper-Poisson regression model for overdispersed and underdispersed count data,
A.J. Sáez-Castillo and A. Conde-Sánchez, in Computational Statistics & Data Analysis (2013)
Keywords: Regression model; Count data; Hyper-Poisson; Overdispersion; Underdispersion;

M estimators based on the probability integral transformation with applications to count data,
Marina Valdora and Víctor Yohai, in Statistics & Probability Letters (2020)
Keywords: Robust estimators; Poisson; Negative binomial; Count data; Probability integral transformation;

Sports and cultural habits by gender: An application using count data models,
Cristina Muñiz, Plácido Rodríguez and María J. Suárez, in Economic Modelling (2014)
Keywords: Sports practice; Cultural events attendance; Count data models; Gender;

A double-hurdle count model for completed fertility data from the developing world,
Alfonso Miranda, from Quantitative Social Science - UCL Social Research Institute, University College London (2010)
Keywords: Completed fertility, count data models, double-hurdle model

Endogenous switching regression model and treatment effects of count-data outcome,
Takuya Hasebe, in Stata Journal (2020)
Keywords: escount, lncount, teescount, self-selection, count data, treatment effects

Robust variable selection of joint frailty model for panel count data,
Weiwei Wang, Xianyi Wu, Xiaobing Zhao and Xian Zhou, in Journal of Multivariate Analysis (2018)
Keywords: Panel count data; Joint frailty model; Variable selection; Quantile regression;

The dimension-wise quadrature estimation of dynamic latent variable models for count data,
Silvia Bianconcini and Silvia Cagnone, in Computational Statistics & Data Analysis (2023)
Keywords: Latent autoregressive models; Count data; Pairwise likelihood; Approximate likelihood inference;