Journal article Open Access

New Log Likelihood Estimation Function

Louangrath, P.


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{
  "publisher": "Zenodo", 
  "DOI": "10.5281/zenodo.1320774", 
  "container_title": "Inter. J. Res. Methodol. Soc. Sci", 
  "language": "eng", 
  "title": "New Log Likelihood Estimation Function", 
  "issued": {
    "date-parts": [
      [
        2015, 
        6, 
        30
      ]
    ]
  }, 
  "abstract": "<p>This paper provides a New Log-Likelihood Estimator (NLLE) function as a tool for value approximation. We improved the accuracy of the log MLE in two steps (i) determine the log likelihood of a random variable <em>X</em>, and (ii) adjust the estimate by a factor of . In-Sample testing was accomplished by using daily SET100 indices over a period of 60 days. Out-of-sample data were used for confirmatory verification; out-of-sample data came from 5 major stock markets: NASDAQ, DOW, SP500, DAX, and CAC40. Relevant tests used to compare the results of the proposed NLLE include Cramer-Rao Lower Bound (CRLB), Likelihood Ratio Test, Wald statistic, and Lagrange Multiplier (Score Statistic). It was found that NLLE is more efficient than the conventional MLE. It gives practitioners a better tool for value estimation in many fields of natural and social sciences.</p>", 
  "author": [
    {
      "family": "Louangrath, P."
    }
  ], 
  "page": "36-47", 
  "volume": "1", 
  "version": "1A", 
  "type": "article-journal", 
  "issue": "2", 
  "id": "1320774"
}
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