From Fractal Geometry to Statistical Fractal


  • Roberto N. Padua
  • Mark S. Borres University of San Jose-Recoletos



fractal geometry, fractal statistics, fractal dimension, scale- invariance, self- similarity, probability distribution


The development from fractal geometry to fractal statistics was established in this paper. Interesting features such as self similarity, scale invariance, and the spacefilling property of objects (fractal dimension) of fractal geometry provided an enormous groundwork to build a link towards the statistical paradigm since most data sets are endowed with its non-normal and irregular characteristic. A new probability distribution called fractal distribution was modeled to accommodate this non-normal conforming characteristic of most data sets and sample investigations were presented at the end of the paper.

Author Biographies

Roberto N. Padua

Dr. Roberto Natividad Padua, scientist, received his PhD in Mathematical Statistics from Clemson University, South Carolina, USA under the Fullbright-Hays scholarship grant. He is an accomplished author, a multi-awarded researcher and an internationally acclaimed lectured. Dr. Padua ia a former Commissioner of CHED and currently a consultant to several State and Private Universities, conducting lectures on research and Fractal Statistics. Dr. Padua is a Summa cum Laude, BS in Mathematics Teaching graduate from the Philippine Normal College under the National Science Development Board (NSDB) program. He obtained his MS in Mathematics Education Degree from the Centro Escolar University as a Presidential Scholar

Mark S. Borres, University of San Jose-Recoletos

graduated Bachelor of Science in Mathematics–major in Pure Mathematics at the University of the Philippines, Cebu College. Since 2009, he worked for the University of San Jose- Recoletos as a faculty member of the College of Arts and Sciences and handled Mathematics subjects such as College Algebra, Advanced Algebra, Abstract Algebra, Analytical Geometry, Euclidean geometry, Trigonometry, Business Mathematics, Linear Programming, Mathematics of Investment, Discrete Structure, and Statistics across colleges.


Akinyemi, Gbenga M. and Abiddin, Norhasni Zainal. (2013). Human Capital Developments an Interdisciplinary Approach for Individual,
Organization Advancement and Economic Improvement”, Asian Social Science.

Barnsley, M. (1988). Fractals Everywhere. San Diego, CA: Academic Press Inc.

Borres, M. et al. (2013). Some Results on Multifractal Spectral Analysis. Unpublished manuscript.

D. Rendon. (2003). Wavelet based estimation of the fractal dimension in fBm images, First International IEEE EMBS Conference on Neural Engineering 2003 Conference Proceedings CNE-03,

Li, Q., et al. (2002).Computer vision based system for apple surface defect detection, Computers and Electronics in Agriculture.

Padua, R., et al. (2013). Statistical Fractal Inference. Unpublished manuscript.

Padua, R., et al. (2013). Statistical Analysis of Fractal Observations: Applications in Education and in Poverty Estimation. Unpublished manuscript.

Sun, W., et al. (2006).Fractal analysis of remotely sensed images: A review of methods and Applications.




How to Cite

Padua, R. N., & Borres, M. S. (2013). From Fractal Geometry to Statistical Fractal. Recoletos Multidisciplinary Research Journal, 1(1).




Most read articles by the same author(s)

1 2 > >>