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Pregled bibliografske jedinice broj: 470305

Statistical analysis of Pearson diffusions with heavy-tailed marginal distributions


Šuvak, Nenad
Statistical analysis of Pearson diffusions with heavy-tailed marginal distributions, 2010., doktorska disertacija, Prirodoslovno matematički fakultet, Matematički odjel, Zagreb


CROSBI ID: 470305 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
Statistical analysis of Pearson diffusions with heavy-tailed marginal distributions

Autori
Šuvak, Nenad

Vrsta, podvrsta i kategorija rada
Ocjenski radovi, doktorska disertacija

Fakultet
Prirodoslovno matematički fakultet, Matematički odjel

Mjesto
Zagreb

Datum
29.04

Godina
2010

Stranica
162

Mentor
Leonenko, Nikolai ; Benšić, Mirta ; Huzak, Miljenko

Ključne riječi
Parameter estimation; Pearson diffusion; Spectral representation; Statistical test for distributional assumptions; Transition density

Sažetak
This PhD thesis presents some new results on spectral properties and statistical analysis of ergodic diffusions with heavy-tailed stationary distributions from the Pearson family. In particular, Fisher-Snedecor, reciprocal gamma and Student diffusion processes are treated. For these three diffusions the spectral representation of the transition density is derived and problems of parameter estimation and testing statistical hypothesis about the stationary distribution are considered. Unknown parameters of the stationary distribution of the particular heavy-tailed Pearson diffusion are estimated by the method of moments. This method here provides consistent and asymptotically normal estimators given in the explicit form. Moreover, for all observed cases asymptotic covariance matrices are explicitly calculated. Expressions for elements of the asymptotic covariance matrices are determined by using the closed-form expressions for the spectral representations of the transition densities and orthogonality of solutions of the corresponding Sturm-Liouville equation. The consistent estimator of the autocorrelation parameter is derived by the generalized method of moments (GMM) based on the Pearson's sample correlation function. Statistical test for assumptions about the stationary distribution of the particular heavy-tailed Pearson diffusion is constructed by the GMM approach and relies on the moment condition based on the orthogonality property of the corresponding polynomial eigenfunctions: Fisher-Snedecor polynomials related to Fisher-Snedecor diffusion, Bessel polynomials related to reciprocal gamma diffusion and Routh-Romanovski polynomials related to Student diffusion. It is proved that the constructed test statistics has chi-square distribution with the number of degrees of freedom coinciding with the number of orthogonal polynomials used in the underlying moment condition.

Izvorni jezik
Engleski

Znanstvena područja
Matematika



POVEZANOST RADA


Projekti:
010-0101195-1048 - Modeli za ocjenu rizičnosti poslovanja poduzeća (Šarlija, Nataša, MZOS ) ( CroRIS)
235-2352818-1039 - Statistički aspekti problema procjene u nelinearnim parametarskim modelima (Benšić, Mirta, MZOS ) ( CroRIS)

Ustanove:
Sveučilište u Osijeku, Odjel za matematiku

Profili:

Avatar Url Mirta Benšić (mentor)

Avatar Url Nenad Šuvak (autor)

Avatar Url Miljenko Huzak (mentor)


Citiraj ovu publikaciju:

Šuvak, Nenad
Statistical analysis of Pearson diffusions with heavy-tailed marginal distributions, 2010., doktorska disertacija, Prirodoslovno matematički fakultet, Matematički odjel, Zagreb
Šuvak, N. (2010) 'Statistical analysis of Pearson diffusions with heavy-tailed marginal distributions', doktorska disertacija, Prirodoslovno matematički fakultet, Matematički odjel, Zagreb.
@phdthesis{phdthesis, author = {\v{S}uvak, Nenad}, year = {2010}, pages = {162}, keywords = {Parameter estimation, Pearson diffusion, Spectral representation, Statistical test for distributional assumptions, Transition density}, title = {Statistical analysis of Pearson diffusions with heavy-tailed marginal distributions}, keyword = {Parameter estimation, Pearson diffusion, Spectral representation, Statistical test for distributional assumptions, Transition density}, publisherplace = {Zagreb} }
@phdthesis{phdthesis, author = {\v{S}uvak, Nenad}, year = {2010}, pages = {162}, keywords = {Parameter estimation, Pearson diffusion, Spectral representation, Statistical test for distributional assumptions, Transition density}, title = {Statistical analysis of Pearson diffusions with heavy-tailed marginal distributions}, keyword = {Parameter estimation, Pearson diffusion, Spectral representation, Statistical test for distributional assumptions, Transition density}, publisherplace = {Zagreb} }




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