Algorithm for Finding the Proper Continuous Distribution Function to a Unimodal Empirical Distribution Function

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Algorithm for Finding the Proper Continuous Distribution Function to a Unimodal Empirical Distribution Function

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Abstract

We present an algorithm containing the first step towards solving one of the Fundamental Problems of Non-parametric Mathematical Statistics: determining the distribution of an unknown unimodal continuous population from which we have a large random sample of discrete observations. We will present the “algorithm of non-fitting” with the help of which, by using the so-called relative increment functions as auxiliary functions, one can eliminate a large class of classical continuous unimodal distributions which our population does not belong to. In the remaining class of unimodal and smooth distributions one can approximate the distribution of the population in question. The algorithm is illustrated in three numerical examples.

Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Dr. Szabo. 1970. "Algorithm for Finding the Proper Continuous Distribution Function to a Unimodal Empirical Distribution Function". Global Journal of Science Frontier Research GJSFR Volume 10 (GJSFR Volume 10 Issue 5).

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Journal Specifications

Crossref Journal DOI 10.17406/GJSFR

Print ISSN 0975-5896

e-ISSN 2249-4626

Keywords
Version of record

v1.2

Issue date
September 14, 2010

Language
English
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Algorithm for Finding the Proper Continuous Distribution Function to a Unimodal Empirical Distribution Function

Dr. Szabo
Dr. Szabo Debrecen University