Semiparametric estimation for count data through weighted distributions
DOI10.1016/j.jspi.2009.04.013zbMath1168.62032OpenAlexW1982498442MaRDI QIDQ2272118
Célestin C. Kokonendji, Narayanaswamy Balakrishnan, Tristan Senga Kiessé
Publication date: 5 August 2009
Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.jspi.2009.04.013
dispersionbandwidth selectionmultiplicative correction factorzero-proportiondiscrete kernel methoddiscrete weighted distribution
Asymptotic properties of parametric estimators (62F12) Density estimation (62G07) Asymptotic properties of nonparametric inference (62G20) Point estimation (62F10) Nonparametric inference (62G99)
Related Items (20)
Cites Work
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- On modeling count data: a comparison of some well-known discrete distributions
- Beta kernel estimators for density functions
- On Hinde-Demétrio regression models for overdispersed count data
- A class of weighted Poisson processes
- Asymptotically optimal bandwidth selection for kernel density estimators from randomly right-censored samples
- Nonparametric density estimation with a parametric start
- Connections of the Poisson weight function to overdispersion and underdispersion
- On some properties of a class of weighted quasi-binomial distributions
- Recent Developments in Nonparametric Density Estimation
- Some heuristics of kernel based estimators of ratio functions
- Multivariate binary discrimination by the kernel method
- Density estimation using inverse and reciprocal inverse Gaussian kernels
- Discrete triangular distributions and non-parametric estimation for probability mass function
- Univariate Discrete Distributions
- Count Data Distributions
- A Useful Distribution for Fitting Discrete Data: Revival of the Conway–Maxwell–Poisson Distribution
- Maximum Likelihood Estimation of Misspecified Models
- Probability density function estimation using gamma kernels
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