Simple method for inference in inverse Ising problem using full data

Hirohito Kiwata

Physica A: Statistical Mechanics and its Applications, 2015, vol. 436, issue C, 321-326

Abstract: We consider inference in the inverse Ising problem using full data, which means incorporating sets of spin configurations. We approximate the Boltzmann distribution of the system to generate a frequency distribution derived from the given data. Then, the ratio between two Boltzmann distributions with different spin configurations eliminates the partition function and we obtain linear equations which can be solved to yield statistical parameters. Our method is applicable to cases where the absolute values of the coupling parameters and external fields are large. Compared to pseudolikelihood maximization, the accuracy of the inference obtained from our method is similar, although our approach is less labor intensive.

Keywords: Inverse Ising problem; Frequency distribution; Overdetermined system; Pseudolikelihood maximization (search for similar items in EconPapers)
Date: 2015
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378437115003945
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

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:436:y:2015:i:c:p:321-326

DOI: 10.1016/j.physa.2015.04.026

Access Statistics for this article

Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis

More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().