Search Results - subject:"generalized inverse Gaussian"

An expectation-maximization algorithm for the exponential-generalized inverse Gaussian regression model with varying dispersion and shape for modelling the aggregate claim amount

Tzougas, George; Jeong, Himchan - In: Risks 9 (2021) 1, pp. 1-17

This article presents the Exponential-Generalized Inverse Gaussian regression model with varying dispersion and shape …

Persistent link: https://www.econbiz.de/10013200689

An expectation-maximization algorithm for the exponential-generalized inverse Gaussian regression model with varying dispersion and shape for modelling the aggregate claim amount

Tzougas, George; Jeong, Himchan - In: Risks : open access journal 9 (2021) 1/19, pp. 1-17

This article presents the Exponential-Generalized Inverse Gaussian regression model with varying dispersion and shape …

Persistent link: https://www.econbiz.de/10012423047

Conditional tail risk measures for the skewed generalised hyperbolic family

Ignatieva, Ekaterina; Landsman, Zinoviy - In: Insurance / Mathematics & economics 86 (2019), pp. 98-114

Persistent link: https://www.econbiz.de/10012058838

Poisson-driven stationary Markov models

Anzarut, Michelle; Mena, Ramsés H.; Nava, Consuelo Rubina - In: Journal of business & economic statistics : JBES ; a … 36 (2018) 4, pp. 684-694

Persistent link: https://www.econbiz.de/10012249233

Bayesian Estimation of Generalized Hyperbolic Skewed Student GARCH Models

Deschamps, Philippe J. - Departement für Quantitative Wirtschaftsforschung, … - 2011

Efficient posterior simulators for two GARCH models with generalized hyperbolic disturbances are presented. The first model, GHt-GARCH, is a threshold GARCH with a skewed and heavy-tailed error distribution; in this model, the latent variables that account for skewness and heavy tails are...

Persistent link: https://www.econbiz.de/10009367387

Gibbs Sampling Methods for Bayesian Quantile Regression

Kozumi, Hideo; Kobayashi, Genya - Graduate School of Business Administration, Kobe University - 2009

accomplished by sampling from either normal or generalized inverse Gaussian distribution. We also discuss some possible extensions …

Persistent link: https://www.econbiz.de/10011114763

Study of compound generalized Nakagami–generalized inverse Gaussian distribution and related densities: application to ultrasound imaging

Gupta, Abhinav; Karmeshu - In: Computational Statistics 30 (2015) 1, pp. 81-96

<Para ID="Par1">A new theoretical probability distribution generalized Nakagami–generalized inverse Gaussian … distribution is a composite distribution derived by compounding generalized Nakagami (GN) and generalized inverse Gaussian (GIG … efficacy of proposed GN–GIGD in relation to Nakagami Gamma and Nakagami–generalized inverse Gaussian distributions is …

Persistent link: https://www.econbiz.de/10011241309

Variance-mean mixture of the multivariate skew normal distribution

Arslan, Olcay - In: Statistical Papers 56 (2015) 2, pp. 353-378

–mean mixture distributions class. The new class results from a variance-mean mixture of the skew normal and the generalized inverse … Gaussian distributions. The new class is very flexible in terms of heavy tails and skewness and many of the widely used …

Persistent link: https://www.econbiz.de/10011241323

Multivariate Skew-Normal Generalized Hyperbolic distribution and its properties

Vilca, Filidor; Balakrishnan, N.; Zeller, Camila Borelli - In: Journal of Multivariate Analysis 128 (2014) C, pp. 73-85

The Generalized Inverse Gaussian (GIG) distribution has found many interesting applications; see Jørgensen [24]. This …

Persistent link: https://www.econbiz.de/10011042075

Re-formulation of inverse Gaussian, reciprocal inverse Gaussian, and Birnbaum–Saunders kernel estimators

Igarashi, Gaku; Kakizawa, Yoshihide - In: Statistics & Probability Letters 84 (2014) C, pp. 235-246

We reveal the boundary bias problem of Birnbaum–Saunders, inverse Gaussian, and reciprocal inverse Gaussian kernel estimators (Jin and Kawczak, 2003; Scaillet, 2004) and re-formulate these estimators to solve the problem. We investigate asymptotic properties of a new class of asymmetric kernel...

Persistent link: https://www.econbiz.de/10010718805