The Application of Fisher Scoring Algorithm on Parameter Estimation of Normal Distributed Data

Authors

  • Switamy Angnitha Purba Universitas HKBP Nommensen Pematangsiantar

DOI:

https://doi.org/10.32734/jormtt.v3i1.8345

Keywords:

Fisher Scoring, Maximum Likehood, Estimation Parameter

Abstract

In statistics, parameter estimation is the estimation of a population using sample data. A population data certainly has a certain distribution. Fisher Scoring is a form of Newton's method which is commonly used in solving the maximum likelihood equation. The focus of this research is to estimate distributed data using the fisher scoring algorithm

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Published

2021-03-05

How to Cite

[1]
S. A. Purba, “The Application of Fisher Scoring Algorithm on Parameter Estimation of Normal Distributed Data”, J. of Research in Math. Trends and Tech., vol. 3, no. 1, pp. 20-24, Mar. 2021.

Issue

Vol. 3 No. 1 (2021): Journal of Research in Mathematics Trends and Technology (JoRMTT)

Section

Articles

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