Evaluation of the Fourth Millennium Development Goal Realisation using Robust and Nonparametric Tools offered by a Data Depth Concept

• Autorzy: Ewa Kosiorowska , Daniel Kosiorowski , Zygmunt Zawadzki
• Języki publikacji: EN

Abstrakty

EN

We briefly communicate the results of nonparametric and robust evaluation of the effects of the Fourth Millennium Development Goal of the United Nations. The main aim of the goal was reducing by two thirds, from 1990-2015, under five month's child mortality. Our novel analysis was conducted by means of very powerful and user friendly tools offered by the Data Depth Concept being a collection of multivariate techniques basing on multivariate generalizations of quintiles, ranges and order statistics. The results of our analysis are more convincing than the results obtained using classical statistical tools.(original abstract)

Słowa kluczowe

EN

Statistical analysis; Infant mortality; Data depth concept

PL

Analiza statystyczna; Umieralność niemowląt; Koncepcja głębi danych

• Czasopismo: Folia Oeconomica Stetinensia
• Rocznik: 2015
• Tom: 15
• Numer: nr 1
• Strony: 34--52

Twórcy

autor

Ewa Kosiorowska

autor

Daniel Kosiorowski

• Uniwersytet Ekonomiczny w Krakowie

autor

Zygmunt Zawadzki

• Uniwersytet Ekonomiczny w Krakowie

Bibliografia

• Goldenberg L.R., Jobe A.H., (2001), Prospects for research in reproductive health and birth outcomes, "JAMA", 285: 633-639.
• Kosiorowski D., Zawadzki Z., (2014), DepthProc: An r package for robust exploration of multidimensional economic phenomena, http://arxiv.org/abs/1408.4542.
• Li J., Liu R.Y., (2004), New nonparametric tests of multivariate locations and scales using data depth, "Statistical Science", 19 (4): 686-696. [CrossRef]
• Liu R., Parelius J.M., Singh K., (1999), Multivariate analysis by data depth: Descriptive statistics, graphics and inference (with discussion), "The Annals of Statistics", 27: 783-858.
• Maronna R.A., Martin R.D., Yohai V.J., (2006), Robust statistics - theory and methods, Chichester: John Wiley & Sons.
• Mizera I., Müller C.H., (2004), Location-scale depth (with discussion), "Journal of the American Statistical Association", 99: 949-966.
• Mosler K., (2013). Depth statistics. In: Robustness and Complex Data Structures, Festschrift in Honour of Ursula Gather, Ed. C. Becker, R. Fried, S. Kuhnt, 17-34, Springer Verlag.
• United Nations Report. The millennium development goals report 2014, 2014, www.un.org/millenniumgoals/2014.
• Paindavaine D., Van Bever G., (2013), From depth to local depth: a focus on centrality, "Journal of the American Statistical Association", 105: 1105-1119. [Web of Science]
• Petrosjan L.A., Yeung D.W.K., (2012), Subgame Consistent Economic Optimization - An Advanced Cooperative Dynamic Game Analysis, New York: Springer Verlag.
• Rousseeuw P.J., Hubert M., (1999), Regression depth, "Journal of the American Statistical Association", 94: 388-433. [CrossRef]
• Stone M. (2002), How not to measure the efficiency of public services (and how one might), "Journal of Royal Statistical Society A", 3 (165): 405-434. [Web of Science]
• Zuo Y. (2003), Projection Based Depth Functions and Associated Medians, "The Annals of Statistics", 31 (5): 1460-1490. [CrossRef]
• Zuo Y., (2004), Robustness of weighted Lp - depth and Lp median, "Allgemaines Statistisches Archiv", 88: 215-234.
• Zuo Y., He X., (2006), On the limiting distributions of multivariate depth based rank sum statistics and related tests, "The Annals of Statistics", 34: 2879-2896. [CrossRef]

Identyfikatory

DOI

10.1515/foli-2015-0021