Results 61 to 70 of about 5,420,390 (236)

Estimating the Parameters of Mixture Gamma Distributions Using Maximum Likelihood and Bayesian Method [PDF]

المجلة العراقية للعلوم الاحصائية
     This paper focuses on the mixture Gamma distribution and uses the maximum likelihood and Bayesian techniques to estimate its parameters.
Nagham Ibrahim Abdulla Najm, Raya Salim Al_Rassam   +1 more
doaj   +1 more source

When in Doubt, Tax More Progressively? Uncertainty and Progressive Income Taxation

International Economic Review, EarlyView.
ABSTRACT We study the optimal income tax problem under parameter uncertainty about household preferences and wage dynamics. We derive conditions characterizing how such uncertainty affects optimal tax policy. To quantify the effect, we estimate a life‐cycle model using US data and a Bayesian approach.
Minsu Chang, Chunzan Wu
wiley   +1 more source

Overdispersed Nonlinear Regression Models

Austrian Journal of Statistics
In this paper we propose nonlinear regression models in the biparametric family of distributions. In this class of models we propose two new classes of overdispersed nonlinear regression models: the first, defined from the overdispersion family of ...
Edilberto Cepeda-Cuervo, María Victoria Cifuentes   +1 more
doaj   +1 more source

A Non‐Parametric Framework for Correlation Functions on Product Metric Spaces

International Statistical Review, EarlyView.
Summary We propose a non‐parametric framework for analysing data defined over products of metric spaces, a versatile class encountered in various fields. This framework accommodates non‐stationarity and seasonality and is applicable to both local and global domains, such as the Earth's surface, as well as domains evolving over linear time or time ...
Pier Giovanni Bissiri, Bernardo Nipoti, Emilio Porcu, Philip White   +3 more
wiley   +1 more source

On Integral Priors for Multiple Comparison in Bayesian Model Selection

International Statistical Review, EarlyView.
Summary Noninformative priors constructed for estimation purposes are usually not appropriate for model selection and testing. The methodology of integral priors was developed to get prior distributions for Bayesian model selection when comparing two models, modifying initial improper reference priors. We propose a generalisation of this methodology to
Diego Salmerón, Juan Antonio Cano, Christian P. Robert   +2 more
wiley   +1 more source

Bayesian Estimation of Parameters Correlation of Bivariate Poisson Distribution [PDF]

فصلنامه پژوهش‌های اقتصادی ایران, 2016
In this study, based on Bayesian Generalized Linear Models, correlation between the parameters of two Poisson distributions was computed. Due to lack of the closed form for posterior distribution, hierarchical Bayesian statistics using the Metropolis ...
Farzad Eskandari
doaj   +1 more source

Likelihood Estimation for Stochastic Differential Equations with Mixed Effects

Scandinavian Journal of Statistics, EarlyView.
ABSTRACT Stochastic differential equations provide a powerful tool for modelling dynamic phenomena affected by random noise. When time series are observed for several experimental units, it is often the case that some of the parameters vary between the individual experimental units.
Fernando Baltazar‐Larios, Mogens Bladt, Michael Sørensen   +2 more
wiley   +1 more source

Learnable Markov Chain Monte Carlo Sampling Methods for Lattice Gaussian Distribution

IEEE Access, 2019
As a key ingredient of machine learning and artificial intelligence, the sampling algorithms with respect to lattice Gaussian distribution has emerged as an important problem in coding and decoding of wireless communications.
Zheng Wang, Shanxiang Lyu, Ling Liu
doaj   +1 more source

A Bayesian Joint Modeling Using Gaussian Linear Latent Variables for Mixed Correlated Outcomes with Possibility of Missing Values [PDF]

Journal of Statistical Theory and Applications (JSTA), 2016
This paper proposes a Bayesian approach for the analysis of mixed correlated nominal, ordinal and continuous outcomes with possibility of missing values using a variation of Markov Chain Monte Carlo (MCMC) method named Parameter Expanded and ...
Sayed Jamal Mirkamali, Mojtaba Ganjali
doaj   +1 more source

Higher connectivity of fiber graphs of Gr\"obner bases [PDF]

, 2013
Fiber graphs of Gr\"obner bases from contingency tables are important in statistical hypothesis testing, where one studies random walks on these graphs using the Metropolis-Hastings algorithm.
Potka, Samu
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