Search Results

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;

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,

Transition models for count data: a flexible alternative to fixed distribution models,
Moritz Berger and Gerhard Tutz, in Statistical Methods & Applications (2021)
Keywords: Count data, Smoothing, Transition model, Varying coefficients, Zero-inflated model

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

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.

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.

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

Spatial panel count data: modeling and forecasting of urban crimes,
Stephanie Glaser, Robert Jung and Karsten Schweikert, in Journal of Spatial Econometrics (2022)
Keywords: Count data, Spatial panel models, Fixed effects, Predictive modeling

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

Modelling count data with overdispersion and spatial effects,
Susanne Gschlößl and Claudia Czado, in Statistical Papers (2008)
Keywords: Bayesian inference, Count data, Overdispersion, Spatial regression models, Zero inflated models,

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;

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;

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;

Innovation and institutional ownership revisited: an empirical investigation with count data models,
Susanne Berger, Herbert Stocker and Achim Zeileis, in Empirical Economics (2017)
Keywords: Innovation, Institutional ownership, Count data, Hurdle model, Replication

Determinants of Antenatal Care Utilisation in India: A Count Data Modelling Approach,
Arvind Kumar Yadav, Susanta Nag, Pabitra Kumar Jena and Kirtti Paltasingh, in Journal of Development Policy and Practice (2021)
Keywords: India; ANC visits; count data; zero-inflated regression model; NFHS

Is Job Stability Declining in Germany? Evidences from Count Data Models,
Rainer Winkelmann and Klaus Zimmermann, from Institute of Labor Economics (IZA) (1998)
Keywords: labour market flexibility, count data models, job mobility

A flexible time-varying coefficient rate model for panel count data,
Dayu Sun, Yuanyuan Guo, Yang Li, Jianguo Sun and Wanzhu Tu, in Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data (2024)
Keywords: Panel count data, Rate model, Sieve estimation, Time-varying effects

Count data modelling of health insurance and health care utilisation in Nigeria,
Saheed Olayiwola and Kazeem Bayo L.O., in Journal of Economics and Management (2019)
Keywords: health insurance, health care utilisation, count data model

Modelling Work-Related Training and Training Effects Using Count Data Techniques,
Wiji Arulampalam, Alison Booth and Peter Elias, from C.E.P.R. Discussion Papers (1997)
Keywords: Count data models; Hurdle; Selectivity bias; Training endogeneity; Wages Growth

Modeling Work-related Training and Training Effects Using Count Data Techniques,
Wiji Arulampalam, Alison Booth and Peter Elias, from University of Warwick, Department of Economics (1996)
Keywords: Count data models ; hurdle ; training ; skills segmentation ; wages growth

Innovation and Institutional Ownership Revisited: An Empirical Investigation with Count Data Models,
Susanne Berger, Herbert Stocker and Achim Zeileis, from Faculty of Economics and Statistics, Universität Innsbruck (2014)
Keywords: innovation, institutional ownership, count data, hurdle model, replication

Equidispersion and moment conditions for count panel data model,
Yoshitsugu Kitazawa, from Kyushu Sangyo University, Faculty of Economics (2009)
Keywords: count panel data, linear feedback model, equidispersion, implicit operation, crosslinkage moment conditions, GMM, Monte Carlo experiments

A Bivariate Count Data Model for Household Tourism Demand,
Jörgen Hellström, from Umeå University, Department of Economics (2002)
Keywords: Integer-valued data; Bivariate hurdle model; Inflated counts; Truncation; Simulated maximum likelihood; Tourism demand.

Counting on count data models,
Rainer Winkelmann, in IZA World of Labor (2015)
Keywords: Poisson regression, negative binomial distribution, zero-inflation, hurdle model

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 Longitudinal Count Data with Missing Values: A Comparative Study,
Fatma El Zahraa S. Salama, Ahmed M. Gad and Amany Mousa, in Academic Journal of Applied Mathematical Sciences (2016)
Keywords: Count data; Generalized estimating equation; longitudinal data; Missing data; Missingness mechanisms; Multiple imputations; Poisson model.

A Theoretical Foundation for Count Data Models,
Daniel Hellerstein and Robert Mendelsohn, from University Library of Munich, Germany (1993)
Keywords: count data, repeat discrete choice, travel cost analysis, welfare analysis.

Multilevel multivariate modelling of legislative count data, with a hidden Markov chain,
Francesco Lagona, Antonello Maruotti and Fabio Padovano, from HAL (2015)
Keywords: Multivariate count data,Hidden Markov models,Longitudinal data,Multilevel models,Political legislation cycles

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

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

The Demand of Car Rentals: a Microeconometric Approach with Count Models and Survey Data,
António Menezes and Ainura Uzagalieva, in Review of Economic Analysis (2013)
Keywords: Count Data Models, Survey Data, Tourism, Market Demand, Car Rentals, Tax Rates

Probabilistic Frontier Regression Models for Count Type Output Data,
Meena Badade and T. V. Ramanathan, in Journal of Quantitative Economics (2022)
Keywords: COM-Poisson distribution, Count-type output data, Crime data, Probabilistic frontier regression models, Technical efficiency

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;

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

The Selection of an Appropriate Count Data Model for Modelling Health Insurance and Health Care Demand: Case of Indonesia,
Budi Hidayat and Subhash Pokhrel, in IJERPH (2009)
Keywords: health insurance; demand for health care; endogeneity; count data models

Modelling financial transaction price movements: a dynamic integer count data model,
Roman Liesenfeld, Ingmar Nolte and Winfried Pohlmeier, from Springer (2008)
Keywords: Financial transaction prices, Autoregressive conditional multinomial model, GLARMA, Count data, Market microstructure effects

Modelling financial transaction price movements: a dynamic integer count data model,
Roman Liesenfeld, Ingmar Nolte and Winfried Pohlmeier, in Empirical Economics (2006)
Keywords: Financial transaction prices, Autoregressive conditional multinomial model, GLARMA, Count data, Market microstructure effects, C22, C25, G10,

Modeling Zero Inflation in Count Data Time Series with Bounded Support,
Tobias A. Möller, Christian H. Weiß, Hee-Young Kim and Andrei Sirchenko, in Methodology and Computing in Applied Probability (2018)
Keywords: Binomial distribution, Count data time series, Hidden Markov model, Markov model, Zero inflation

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.

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

Fitting N-mixture models to count data with unmodeled heterogeneity: Bias, diagnostics, and alternative approaches,
Adam Duarte, Michael J. Adams and James T. Peterson, in Ecological Modelling (2018)
Keywords: Abundance; Count data; Detection; Goodness of fit; Monitoring; N-mixture model;

K-aggregated transformation of discrete distributions improves modeling count data with excess ones,
Can Zhou, Yan Jiao and Joan Browder, in Ecological Modelling (2019)
Keywords: Count data; Rare event; Species distribution; Bayesian; Generalized linear model;

A Spatio-Temporal Model and Inference Tools for Longitudinal Count Data on Multicolor Cell Growth,
Qiao PuXue, Mølck Christina, Davide Ferrari and Hollande Frédéric, in The International Journal of Biostatistics (2018)
Keywords: spatio-temporal lattice model, count data, multicolor cell growth

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

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

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

FIML estimation of an endogenous switching model for count data,
Alfonso Miranda, in Stata Journal (2004)
Keywords: count models, endogenous switch, sample selection

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

The chi-squared goodness-of-fit test for count-data models,
Miguel Manjon Antolin and Oscar Martinez, in Stata Journal (2014)
Keywords: chi2gof, Andrews’s chi-squared goodness-of-fit test, m-tests, count-data models

Semi-parametric approach for modelling overdispersed count data with application to Industry 4.0,
S. Bonnini, M. Borghesi and M. Giacalone, in Socio-Economic Planning Sciences (2024)
Keywords: Generalized linear model; Count data; Overdispersion; Permutation test; Industry 4.0; Public policy;

Bias in instrumental-variable estimators of fixed-effect models for count data,
Koen Jochmans, from HAL (2022)
Keywords: Count data,Bias,Fixed effects,Inconsistency,Instrumental variable,Multiplicative-error model,Poisson

Bias in instrumental-variable estimators of fixed-effect models for count data,
Koen Jochmans, in Economics Letters (2022)
Keywords: Count data; Bias; Fixed effects; Inconsistency; Instrumental variable; Multiplicative-error model; Poisson;

Introducing LASSO-type penalisation to generalised joint regression modelling for count data,
Hendrik van der Wurp and Andreas Groll, in AStA Advances in Statistical Analysis (2023)
Keywords: Count data regression, FIFA world cups, Football penalisation, Joint modelling, Regularisation

A Dynamic Integer Count Data Model for Financial Transaction Prices,
Winfried Pohlmeier and Roman Liesenfeld, from University of Konstanz, Center of Finance and Econometrics (CoFE) (2003)
Keywords: Autoregressive conditional multinomial model, GLARMA, transaction prices, count data, market microstructure

Some additional moment conditions for a dynamic count panel data model,
Yoshitsugu Kitazawa, from Kyushu Sangyo University, Faculty of Economics (2008)
Keywords: count panel data, linear feedback model, implicit operation, moment conditions, generalized method of moments, Monte Carlo experiments

A forward demeaning transformation for a dynamic count panel data model,
Yoshitsugu Kitazawa, from Kyushu Sangyo University, Faculty of Economics (2010)
Keywords: forward demeaning; linear feedback model; strictly exogenous explanatory variables; count panel data

Truncation and Endogenous Stratification in Various Count Data Models for Recreation Demand Analysis,
Tomoaki Nakatani and Kazuo Sato, from Stockholm School of Economics (2005)
Keywords: Count data models; Endogenous stratification; Overdispersion; Recreation demand analysis; Consumer's surplus

Inference of a time-varying coefficient regression model for multivariate panel count data,
Yuanyuan Guo, Dayu Sun and Jianguo Sun, in Journal of Multivariate Analysis (2022)
Keywords: B-splines; Estimating equation; Marginal mean model; Multivariate panel count data; Time-varying coefficients;

Bias In Instrumental-Variable Estimators Of Fixed-Effect Models For Count Data,
Koen Jochmans, from Toulouse School of Economics (TSE) (2021)
Keywords: Count data; Bias; Fixed effects; Inconsistency; Instrumental variable;; Multiplicative-error model; Poisson.

Mixture models for capture-recapture count data,
Dankmar Böhning, Ekkehart Dietz, Ronny Kuhnert and Dieter Schön, in Statistical Methods & Applications (2005)
Keywords: Counting Distribution Model, capture-recapture, truncated count distribution, finite mixture models

Modelling and Diagnostics of Spatially Autocorrelated Counts,
Robert Jung and Stephanie Glaser, in Econometrics (2022)
Keywords: count data models; spatial econometrics; spatial autocorrelation; firm location choice

Generalised count distributions for modelling parity,
Bilal Barakat, in Demographic Research (2017)
Keywords: fertility, parity, count data model, discrete probability distributions

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

Three-level zero-inflated Conway–Maxwell–Poisson regression model for analyzing dispersed clustered count data with extra zeros,
Somayeh Ghorbani Gholiabad, Abbas Moghimbeigi and Javad Faradmal, in Sankhya B: The Indian Journal of Statistics (2021)
Keywords: Clustered count data, Mixed effect model, Multilevel data, Over-dispersion, Zero-inflated Conway–Maxwell–Poisson model

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

Count (and count-like) data in finance,
Jonathan B. Cohn, Zack Liu and Malcolm I. Wardlaw, in Journal of Financial Economics (2022)
Keywords: Empirical methods; Count data; Poisson regression;

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

Finding market structure by sales count dynamics—Multivariate structural time series models with hierarchical structure for count data—,
Nobuhiko Terui, Masataka Ban and Toshihiko Maki, in Annals of the Institute of Statistical Mathematics (2010)
Keywords: Count data, Generalized linear model, Hierarchical market structure, MCMC, Poisson–multinomial distribution, Predictive density, POS time series,

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,

‘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,

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;

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

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

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,

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

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;

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

Predicted probabilities for count models,
J. Scott Long and Jeremy Freese, in Stata Journal (2001)
Keywords: predicted probabilities, count models

Trip misreporting forecast using count data model in a GPS enhanced travel survey,
Md. Sakoat Hossan, Hamidreza Asgari and Xia Jin, in Transportation (2018)
Keywords: Trip misreporting, Count data model, Interaction effect, Trip generation model, Household travel survey, Global positioning system

Multivariate count data models for adoption of new transport modes in an organization-based context,
Georges Sfeir, Maya Abou-Zeid and Isam Kaysi, in Transport Policy (2020)
Keywords: Multivariate count data models; Integrated choice and latent variable model (ICLV); Multimodality; Shared-ride taxi; Shuttle; Organization;

An Approach to Analyze Longitudinal Zero-Inflated Microbiome Count Data Using Two-Stage Mixed Effects Models,
Jian Wang, Cielito C. Reyes-Gibby and Sanjay Shete, in Statistics in Biosciences (2021)
Keywords: Oral microbiome, Two-stage model, Zero-inflated negative binomial mixed effects model, Longitudinal count data

A simple and useful regression model for underdispersed count data based on Bernoulli–Poisson convolution,
Marcelo Bourguignon, Diego I. Gallardo and Rodrigo M. R. Medeiros, in Statistical Papers (2022)
Keywords: Count data, EM-algorithm, Mean and dispersion models, Poisson distribution, Regression models, Underdispersion

Using Non-parametric Count Model for Credit Scoring,
Sami Mestiri and Abdeljelil Farhat, in Journal of Quantitative Economics (2021)
Keywords: Count data, Non-parametric model, Credit scoring, Prediction

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

A negative binomial model and moment conditions for count panel data,
Yoshitsugu Kitazawa, from Kyushu Sangyo University, Faculty of Economics (2009)
Keywords: count panel data, predetermined explanatory variable, linear feedback model, overdispersion, negative binomial model, implicit operation, cross-linkage moment conditions, GMM, Monte Carlo experiments

Model misspecification effects in clustered count data analysis,
Vandna Jowaheer, in Statistics & Probability Letters (2006)
Keywords: Clustered count data Mixed effects Quasi-likelihood Efficiency Regression effects Variance of the random effects

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

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

Demand for cigarettes in Turkey: an application of count data models,
Abdulbaki Bilgic, Wojciech Florkowski and Cuma Akbay, in Empirical Economics (2010)
Keywords: Turkey, Cigarette demand, Household, Excess zero observations, Count data, Excise tax, D11, D12,