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  • Search: person:"Fung, Thomas"
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Year of publication
Subject
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Fashion 2 Internet marketing 2 Jugendliche 2 Mode 2 Online-Marketing 2 Social Web 2 Social web 2 Youth 2 Asymptotic tail dependence coefficient 1 Bivariate skew-t distribution 1 Convergence rate 1 DIC 1 JAGS 1 Maximum likelihood estimation 1 Mixing representation 1 Normal Variance–Mean distribution 1 Quantile function 1 Variance-Gamma distribution 1
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Online availability
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Undetermined 9 Free 1
Type of publication
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Article 13 Book / Working Paper 1
Type of publication (narrower categories)
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Article in journal 1 Aufsatz in Zeitschrift 1
Language
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Undetermined 12 English 2
Author
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Fung, Thomas 13 Seneta, Eugene 11 Wang, Joanna J.J. 2 Finlay, Richard 1 Fung, Thomas T. 1 Robinson, John 1 Sinha, Indrajit Jay 1 Sinha, Jay I. 1
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Published in...
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Statistics & Probability Letters 4 International Statistical Review 3 Journal of Multivariate Analysis 2 Computational Statistics & Data Analysis 1 Operations research letters 1 Quantitative Finance 1 Rutgers business review 1
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Source
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RePEc 11 ECONIS (ZBW) 2 OLC EcoSci 1
Showing 1 - 10 of 14
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How Social Media Micro-Influencers Are Disrupting the Business of Youth Fashion
Sinha, Indrajit Jay; Fung, Thomas - 2021
Recent years have seen a veritable surge in the popularity of social media micro-influencers among the younger generations like Millennials and Generation-Z. These amateur micro-influencers have achieved a modicum of fame through their charismatic appeal and niche expertise, by focusing on a...
Persistent link: https://www.econbiz.de/10013230762
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How social media micro-influencers are disrupting the business of youth fashion
Sinha, Jay I.; Fung, Thomas T. - In: Rutgers business review 6 (2021) 1, pp. 44-50
Persistent link: https://www.econbiz.de/10012626138
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Convergence rate to a lower tail dependence coefficient of a skew-t distribution
Fung, Thomas; Seneta, Eugene - In: Journal of Multivariate Analysis 128 (2014) C, pp. 62-72
We examine the rate of decay to the limit of the tail dependence coefficient of a bivariate skew-t distribution. This distribution always displays asymptotic tail dependence. It contains as a special case the usual bivariate symmetric t distribution, and hence is an appropriate (skew) extension....
Persistent link: https://www.econbiz.de/10010776638
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The Deviance Information Criterion in Comparison of Normal Mixing Models
Fung, Thomas; Wang, Joanna J.J.; Seneta, Eugene - In: International Statistical Review 82 (2014) 3, pp. 411-421
type="main" xml:id="insr12063-abs-0001" <title type="main">Summary</title>Model selection from several non-nested models by using the deviance information criterion within Bayesian inference Using Gibbs Sampling (BUGS) software needs to be treated with caution. This is particularly important if one can specify a model in...
Persistent link: https://www.econbiz.de/10011153022
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Contaminated Variance–Mean mixing model
Fung, Thomas; Wang, Joanna J.J.; Seneta, Eugene - In: Computational Statistics & Data Analysis 67 (2013) C, pp. 258-267
The Generalised Normal Variance–Mean (GNVM) model in which the mixing random variable is Gamma distributed is considered. This model generalises the popular Variance-Gamma (VG) distribution. This GNVM model can be interpreted as the addition of noise to a (skew) VG base. The discussion is...
Persistent link: https://www.econbiz.de/10010871309
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Autocorrelation Functions
Finlay, Richard; Fung, Thomas; Seneta, Eugene - In: International Statistical Review 79 (2011) 2, pp. 255-271
Persistent link: https://www.econbiz.de/10009216074
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The bivariate normal copula function is regularly varying
Fung, Thomas; Seneta, Eugene - In: Statistics & Probability Letters 81 (2011) 11, pp. 1670-1676
We derive the rate of decay of the tail dependence of the bivariate normal distribution and establish its link with regularly varying functions. This result is an initial step in explaining the discrepancy between a zero asymptotic tail dependence coefficient and mass in the tail of a joint...
Persistent link: https://www.econbiz.de/10009292570
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Tail dependence and skew distributions
Fung, Thomas; Seneta, Eugene - In: Quantitative Finance 11 (2010) 3, pp. 327-333
Persistent link: https://www.econbiz.de/10009214998
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Tail dependence for two skew t distributions
Fung, Thomas; Seneta, Eugene - In: Statistics & Probability Letters 80 (2010) 9-10, pp. 784-791
We examine two bivariate skew t distributions, both of which generalize the bivariate symmetric t distribution. The second, based on the bivariate skew normal distribution, always displays positive asymptotic lower tail dependence. The difference is associated with the varying tail behavior of...
Persistent link: https://www.econbiz.de/10008488243
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Extending the multivariate generalised t and generalised VG distributions
Fung, Thomas; Seneta, Eugene - In: Journal of Multivariate Analysis 101 (2010) 1, pp. 154-164
The GGH family of multivariate distributions is obtained by scale mixing on the Exponential Power distribution using the Extended Generalised Inverse Gaussian distribution. The resulting GGH family encompasses the multivariate generalised hyperbolic (GH), which itself contains the multivariate t...
Persistent link: https://www.econbiz.de/10008521119
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