IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v526y2019ics0378437119306272.html
   My bibliography  Save this article

Comparisons of log-normal mixture and Pareto tails, GB2 or log-normal body of Romania’s all cities size distribution

Author

Listed:
  • Băncescu, Irina
  • Chivu, Luminiţa
  • Preda, Vasile
  • Puente-Ajovín, Miguel
  • Ramos, Arturo

Abstract

Modeling demographic data has been on the agenda of statisticians for many years. Some of the distributions used are Pareto, reverse Pareto, q-exponential and log-normal models. An approach to this problem is to consider three statistical models: one for the upper tail, one for the middle range, and another for the lower tail. This paper deals with the size distribution of urban and rural agglomerations in Romania for the 1992–2017 period, by comparing the recently introduced three log-normal mixture (3LN), Pareto tails log-normal (PTLN), and threshold double Pareto Generalized Beta of second kind (tdPGB2) models. The tdPGB2 statistical model has the PTLN distribution as a limiting case. The maximum likelihood estimates of the distributions are computed, and goodness-of-fit tests are performed using the Kolmogorov–Smirnov (KS), Cramér–von Mises (CM) and Anderson–Darling (AD) statistics. Also, we use the Vuong and Bayes factor log-likelihood tests. Using both graphical and formal statistical tests, our results rigorously confirm that the 3LN model is statistically equivalent to PTLN and tdPGB2 distributions, the preferred model being the PTLN probability law. Both the PTLN and tdPGB2 distributions have Pareto tails but the 3LN model does not. All the three models prove to be very well suited parameterizations of Romania’s city size data.

Suggested Citation

  • Băncescu, Irina & Chivu, Luminiţa & Preda, Vasile & Puente-Ajovín, Miguel & Ramos, Arturo, 2019. "Comparisons of log-normal mixture and Pareto tails, GB2 or log-normal body of Romania’s all cities size distribution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 526(C).
    • Handle: RePEc:eee:phsmap:v:526:y:2019:i:c:s0378437119306272
    DOI: 10.1016/j.physa.2019.04.253
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437119306272
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2019.04.253?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Tomaschitz, Roman, 2020. "Multiply broken power-law densities as survival functions: An alternative to Pareto and lognormal fits," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 541(C).
    2. Campolieti, Michele & Ramos, Arturo, 2021. "The distribution of strike size: Empirical evidence from Europe and North America in the 19th and 20th centuries," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 563(C).
    3. Milićević Snežana & Petrović Jelena & Đorđević Nataša, 2020. "ICT as a factor of destination competitiveness: The case of the republics of former Yugoslavia," Management & Marketing, Sciendo, vol. 15(3), pages 381-392, September.
    4. Catana, Luigi-Ionut, 2022. "Stochastic orders of multivariate Jones–Larsen distribution family with empirical applications in physics, economy and social sciences," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 603(C).
    5. Peña, Guillermo & Puente-Ajovín, Miguel & Ramos, Arturo & Sanz-Gracia, Fernando, 2022. "Log-growth rates of CO2: An empirical analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 588(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:526:y:2019:i:c:s0378437119306272. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.