Authors:
Emrah AltunDepartment of Mathematics, Bartin University, Bartin, 74100, Turkey

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Morad AlizadehDepartment of Statistics, Faculty of Intelligent Systems Engineering and Data Science, Persian Gulf University, Bushehr, 75169, Iran

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Haitham M. YousofDepartment of Statistics, Mathematics and Insurance, Benha University, Egypt

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G. G. HamedaniDepartment of Mathematics, Statistics and Computer Science, Marquette University, USA

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This study proposes a new family of continuous distributions, called the Gudermannian generated family of distributions, based on the Gudermannian function. The statistical properties, including moments, incomplete moments and generating functions, are studied in detail. Simulation studies are performed to discuss and evaluate the maximum likelihood estimations of the model parameters. The regression model of the proposed family considering the heteroscedastic structure of the scale parameter is defined. Three applications on real data sets are implemented to convince the readers in favour of the proposed models.

  • [1]

    E. Altun. The generalized Gudermannian distribution: inference and volatility modelling. Statistics, 53(2):364386, 2019.

  • [2]

    A. Alzaatreh, C. Lee and F. Famoye. A new method for generating families of continuous distributions. Metron, 71:6379, 2013.

  • [3]

    G. M. Cordeiro and M. de Castro. A new family of generalized distributions. Journal of Statistical Computation and Simulation, 81:883898, 2011.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • [4]

    G. M. Cordeiro, E. M. M. Ortega and D. C. C. da Cunha. The exponentiated generalized class of distributions. J. Data Sci., 11:127, 2013.

  • [5]

    G. M. Cordeiro, M. Alizadeh and E. M. Ortega. The exponentiated half-logistic family of distributions: Properties and applications. Journal of Probability and Statistics, 2014.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • [6]

    G. M. Cordeiro, M. Alizadeh, G. Ozel, B. Hosseini, E. M. M. Ortega and E. Altun. The general-ized odd log-logistic family of distributions: properties, regression models and applications. Journal of Statistical Computation and Simulation, 87(5):908932, 2017.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • [7]

    J. N. D. Cruz, E. M. Ortega and G. M. Cordeiro. The log-odd log-logistic Weibull regres-sion model: modelling, estimation, influence diagnostics and residual analysis. Journal of statistical computation and simulation, 86(8):15161538, 2016.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • [8]

    W. Glänzel. A characterization theorem based on truncated moments and its application to some distribution families. Mathematical Statistics and Probability Theory (Bad Tatzmannsdorf, 1986), Vol. B, Reidel, Dordrecht, 1987, 7584.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • [9]

    W. Glänzel. Some consequences of a characterization theorem based on truncated moments. Statistics: A Journal of Theoretical and Applied Statistics, 21(4):613618, 1990.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • [10]

    I. S. Gradshteyn and I. M. Ryzhik. Table of Integrals. Series, and Products. Academic Press, 2007.

  • [11]

    J. U. Gleaton and J. D. Lynch. Properties of generalized log-logistic families of lifetime distributions. Journal of Probability and Statistical Science, 4(1):5164, 2006.

    • Search Google Scholar
    • Export Citation
  • [12]

    C. A. McGilchrist and C. W. Aisbett. Regression with frailty in survival analysis. Biometrics, 461466, 1991.

  • [13]

    W. Q. Meeker and L. A. Escobar. Statistical methods for reliability data. New York: John Wiley, 1998.

  • [14]

    F. Prataviera, E. M. Ortega, G. M. Cordeiro and A. D. S. Braga. The heteroscedastic odd log-logistic generalized gamma regression model for censored data. Communications in Statistics-Simulation and Computation, 48(6):18151839, 2019.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • [15]

    K. Xu, M. Xie, L. C. Tang and S. L. Ho. Application of neural networks in forecasting engine systems reliability. Applied Soft Computing, 2(4):255268, 2003.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • [16]

    H. M. Yousof, E. Altun, M. Rasekhi, M. Alizadeh, G. G. Hamedani and M. M. Ali. A new life-time model with regression models, characterizations and applications. Communications in Statistics-Simulation and Computation, 48(1):264286, 2019.

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Editors in Chief

Gábor SIMONYI (Rényi Institute of Mathematics)
András STIPSICZ (Rényi Institute of Mathematics)
Géza TÓTH (Rényi Institute of Mathematics) 

Managing Editor

Gábor SÁGI (Rényi Institute of Mathematics)

Editorial Board

  • Imre BÁRÁNY (Rényi Institute of Mathematics)
  • Károly BÖRÖCZKY (Rényi Institute of Mathematics and Central European University)
  • Péter CSIKVÁRI (ELTE, Budapest) 
  • Joshua GREENE (Boston College)
  • Penny HAXELL (University of Waterloo)
  • Andreas HOLMSEN (Korea Advanced Institute of Science and Technology)
  • Ron HOLZMAN (Technion, Haifa)
  • Satoru IWATA (University of Tokyo)
  • Tibor JORDÁN (ELTE, Budapest)
  • Roy MESHULAM (Technion, Haifa)
  • Frédéric MEUNIER (École des Ponts ParisTech)
  • Márton NASZÓDI (ELTE, Budapest)
  • Eran NEVO (Hebrew University of Jerusalem)
  • János PACH (Rényi Institute of Mathematics)
  • Péter Pál PACH (BME, Budapest)
  • Andrew SUK (University of California, San Diego)
  • Zoltán SZABÓ (Princeton University)
  • Martin TANCER (Charles University, Prague)
  • Gábor TARDOS (Rényi Institute of Mathematics)
  • Paul WOLLAN (University of Rome "La Sapienza")

STUDIA SCIENTIARUM MATHEMATICARUM HUNGARICA
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Address: P.O. Box 127, H–1364 Budapest, Hungary
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2021  
Web of Science  
Total Cites
WoS
589
Journal Impact Factor 0,739
Rank by Impact Factor Mathematics 229/332
Impact Factor
without
Journal Self Cites
0,710
5 Year
Impact Factor
0,654
Journal Citation Indicator 0,57
Rank by Journal Citation Indicator Mathematics 287/474
Scimago  
Scimago
H-index
26
Scimago
Journal Rank
0,265
Scimago Quartile Score Mathematics (miscellaneous) (Q3)
Scopus  
Scopus
Cite Score
1,3
Scopus
CIte Score Rank
General Mathematics 193/391 (Q2)
Scopus
SNIP
0,746

2020  
Total Cites 536
WoS
Journal
Impact Factor
0,855
Rank by Mathematics 189/330 (Q3)
Impact Factor  
Impact Factor 0,826
without
Journal Self Cites
5 Year 1,703
Impact Factor
Journal  0,68
Citation Indicator  
Rank by Journal  Mathematics 230/470 (Q2)
Citation Indicator   
Citable 32
Items
Total 32
Articles
Total 0
Reviews
Scimago 24
H-index
Scimago 0,307
Journal Rank
Scimago Mathematics (miscellaneous) Q3
Quartile Score  
Scopus 139/130=1,1
Scite Score  
Scopus General Mathematics 204/378 (Q3)
Scite Score Rank  
Scopus 1,069
SNIP  
Days from  85
submission  
to acceptance  
Days from  123
acceptance  
to publication  
Acceptance 16%
Rate

2019  
Total Cites
WoS
463
Impact Factor 0,468
Impact Factor
without
Journal Self Cites
0,468
5 Year
Impact Factor
0,413
Immediacy
Index
0,135
Citable
Items
37
Total
Articles
37
Total
Reviews
0
Cited
Half-Life
21,4
Citing
Half-Life
15,5
Eigenfactor
Score
0,00039
Article Influence
Score
0,196
% Articles
in
Citable Items
100,00
Normalized
Eigenfactor
0,04841
Average
IF
Percentile
13,117
Scimago
H-index
23
Scimago
Journal Rank
0,234
Scopus
Scite Score
76/104=0,7
Scopus
Scite Score Rank
General Mathematics 247/368 (Q3)
Scopus
SNIP
0,671
Acceptance
Rate
14%

 

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Studia Scientiarum Mathematicarum Hungarica
Language English
French
German
Size B5
Year of
Foundation
1966
Volumes
per Year
1
Issues
per Year
4
Founder Magyar Tudományos Akadémia  
Founder's
Address
H-1051 Budapest, Hungary, Széchenyi István tér 9.
Publisher Akadémiai Kiadó
Publisher's
Address
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Publisher
Chief Executive Officer, Akadémiai Kiadó
ISSN 0081-6906 (Print)
ISSN 1588-2896 (Online)