Add to ORKGA new general fitting method based on the Self-Similar (SS) organization of random sequences is presented. The proposed analytical function helps to fit the response of many complex systems when their recorded data form a self-similar curve. The verified SS principle opens new possibilities for the fitting of economical, meteorological and other complex data when the mathematical model is absent but the reduced description in terms of some universal set of the fitting parameters is necessary. This fitting function is verified on economical (price of a commodity versus time) and weather (the Earth's mean temperature surface data versus time) and for these nontrivial cases it becomes possible to receive a very good fit of initial data set. Th...
In studying the scale invariance of an empirical time series a twofold problem arises: it is necessa...
To cite this version: Dominique Guegan, Zhiping Lu. A note on self-similarity for discrete time seri...
We propose a method to analyze a turbulent sequence focusing on the self-similar properties of the d...
A new general fitting method based on the Self-Similar (SS) organization of random sequences is pres...
A new general fitting method based on the Self-Similar (SS) organization of random sequences is pres...
Many random signals with clearly expressed trends can have selfsimilar properties. In order to see t...
Within Tsallis statistics, a picture is elaborated to treat self-similar time series as a thermodyna...
Introduction A self-similar process is loosely defined as a stochastic process which generates a sa...
In studying the scale invariance of an empirical time series a twofold problem arises: it is necessa...
Introduction A stochastic process Y (t) is defined as self-similar with self-similarity parameter H...
Relying on self-similarities and scale invariances, scientists have started to think about financial...
Statistical self-similarity of random processes in continuous-domains is defined through invariance ...
Abstract: This note surveys some recent results on self-similar Markov processes. Since the research...
This paper presents a generalized approach to the fractal analysis of self-similar random processes ...
This work is concerned with the analysis of self-similar stochastic pro-cesses, where statistical se...
In studying the scale invariance of an empirical time series a twofold problem arises: it is necessa...
To cite this version: Dominique Guegan, Zhiping Lu. A note on self-similarity for discrete time seri...
We propose a method to analyze a turbulent sequence focusing on the self-similar properties of the d...
A new general fitting method based on the Self-Similar (SS) organization of random sequences is pres...
A new general fitting method based on the Self-Similar (SS) organization of random sequences is pres...
Many random signals with clearly expressed trends can have selfsimilar properties. In order to see t...
Within Tsallis statistics, a picture is elaborated to treat self-similar time series as a thermodyna...
Introduction A self-similar process is loosely defined as a stochastic process which generates a sa...
In studying the scale invariance of an empirical time series a twofold problem arises: it is necessa...
Introduction A stochastic process Y (t) is defined as self-similar with self-similarity parameter H...
Relying on self-similarities and scale invariances, scientists have started to think about financial...
Statistical self-similarity of random processes in continuous-domains is defined through invariance ...
Abstract: This note surveys some recent results on self-similar Markov processes. Since the research...
This paper presents a generalized approach to the fractal analysis of self-similar random processes ...
This work is concerned with the analysis of self-similar stochastic pro-cesses, where statistical se...
In studying the scale invariance of an empirical time series a twofold problem arises: it is necessa...
To cite this version: Dominique Guegan, Zhiping Lu. A note on self-similarity for discrete time seri...
We propose a method to analyze a turbulent sequence focusing on the self-similar properties of the d...