Results 251 to 260 of about 366,408 (290)

Estimation of parameters for generalized Gaussian distribution

2014 6th International Symposium on Communications, Control and Signal Processing (ISCCSP), 2014
Shape parameter estimation procedures for generalized Gaussian distribution are considered. It is shown that the existing estimators can be divided into four groups: maximum likelihood algorithm; moment-based methods; entropy matching estimators and global convergence algorithm.
A. A. Roenko, V. V. Lukin, I. Djurovic, M. Simeunovic   +3 more
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On a generalization of Gaussian distribution

Annals of the Institute of Statistical Mathematics, 1978
was first obtained by Subbotin (see Subbotin [15] and Johnson and Kotz [5]). This distribution exhibits many remarkable properties at various points as seen in the works of Box and Tiao [1], Diananda [2] and Johnson and Kotz, op. cit. In this paper, the author tries to characterize this distribution from some other points of view.
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Generalized Inverse Gaussian Distributions and their Wishart Connections

Scandinavian Journal of Statistics, 1998
The matrix generalized inverse Gaussian distribution (MGIG) is shown to arise as a conditional distribution of components of a Wishart distributio n. In the special scalar case, the characterization refers to members of the class of generalized inverse Gaussian distributions (GIGs) and includes the inverse Gaussian distribution among ...
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Rate-distortion results for Generalized Gaussian distributions

2008 IEEE International Conference on Acoustics, Speech and Signal Processing, 2008
In this paper, we provide operational rate-distortion results for memoryless generalized Gaussian sources. Close approximations of the entropy are provided for these sources, after a uniform scalar quantization at low/high resolution. Asymptotic expressions of the distortion for an arbitrary p-th order error measure are also given.
Fraysse, Aurélia, Pesquet-Popescu, Béatrice, Pesquet, Jean-Christophe   +2 more
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Gamma-Generalized Inverse Gaussian Class of Distributions with Applications

Communications in Statistics - Theory and Methods, 2013
n this article, a new family of probability distributions with domain in R+ is introduced. This class can be considered as a natural extension of the exponential-inverse Gaussian distribution in Bhattacharya and Kumar (1986) and Frangos and Karlis (2004).
Gómez Déniz, Emilio, Calderín-Ojeda, Enrique, Sarabia, José María   +2 more
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Modeling neural activity using the generalized inverse Gaussian distribution

Biological Cybernetics, 1997
Spike trains from neurons are often used to make inferences about the underlying processes that generate the spikes. Random walks or diffusions are commonly used to model these processes; in such models, a spike corresponds to the first passage of the diffusion to a boundary, or firing threshold.
Iyengar, Satish, Liao, Qiming
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A NEW MIXTURE MODEL FROM GENERALIZED POISSON AND GENERALIZED INVERSE GAUSSIAN DISTRIBUTION

Far East Journal of Theoretical Statistics, 2017
Summary: In this paper, we propose a new distribution for modeling count datasets with some unique characteristics, obtained by mixing the generalized Poisson distribution (GPD) and the generalized inverse Gaussian distribution (GIGD) and using the framework of the Lagrangian probability distribution.
Olumoh, J. S., Sanni, O. O. M., Ajayi, O. O., Jolayemi, E. T.   +3 more
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Generalized Gaussian distribution based adaptive mixed-norm inversion for non-Gaussian noise

SEG Technical Program Expanded Abstracts 2015, 2015
We propose an generalized Gaussian distribution based adaptive mixed-norm algorithm to deal with non-Gaussian noise that depend on the precision of the tools used for the measurement and the approximate models for seismic and rock-physics modeling. A mixed-norm functional combines the l1 norm and l2 norm is proposed.
Zhiyong Li*, Zhining Liu, Chengyun Song, Guangmin Hu, Jiashu Zhang   +4 more
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Random variate generation for the generalized inverse Gaussian distribution

Statistics and Computing, 2012
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Wheezing sounds detection using multivariate generalized gaussian distributions

2009 IEEE International Conference on Acoustics, Speech and Signal Processing, 2009
A wheeze is a continuous, coarse, whistling sound produced in the respiratory airways during breathing, commonly experienced by persons suffering from asthma. In this paper, we present a new method for the detection of wheezing sounds in the normal breathing sounds. In our study we perform an accurate statistical analysis of breathing signals.
S. Le Cam, A. Belghith, Ch. Collet, F. Salzenstein   +3 more
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