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A Fiducial-based Test for the Equality of Location Parameters

In: MODELING AND ADVANCED TECHNIQUES IN MODERN ECONOMICS

Author

Listed:
  • Gamze Güven
  • Özge Gürer
  • Hatice Samkar
  • Birdal Şenoğlu

Abstract

Motivated by Fisher’s fiducial inference, a new test is proposed for testing the equality of location parameters of Weibull populations when the scale parameters are unequal. It is defined based on the sum of the squared differences between the estimates of location parameters and weighted mean of the estimates of location parameters. In estimating the model parameters, modified maximum likelihood (MML) methodology proposed by Tiku is used. Resulting estimators are asymptotically equivalent to the maximum likelihood (ML) estimators; therefore, they have all the asymptotic properties of the ML estimators, such as unbiasedness, efficiency and consistency. The proposed test is constructed using MML estimators and a pivotal quantity. A comprehensive Monte Carlo simulation study is conducted to compare this test with the corresponding test based on the well-known least squares (LS) estimators with respect to the power criterion. Simulation results show that the proposed test outperforms the LS-based test in terms of the power criterion.

Suggested Citation

  • Gamze Güven & Özge Gürer & Hatice Samkar & Birdal Şenoğlu, 2022. "A Fiducial-based Test for the Equality of Location Parameters," World Scientific Book Chapters, in: Çağdaş Hakan Aladağ & Nihan Potas (ed.), MODELING AND ADVANCED TECHNIQUES IN MODERN ECONOMICS, chapter 5, pages 105-126, World Scientific Publishing Co. Pte. Ltd..
    • Handle: RePEc:wsi:wschap:9781800611757_0005
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    Keywords

    Harmonic Regression; Periodograms; Consumer Price Index; Food Inflation; Turkey; Gaussian Distribution; Europe Union; GDP; Panel Data; Spatial Regression; Measurement Errors; Nonlinear Time Series; Chaotic Time Series; Weibull Distribution; Location Parameters; Fiducial Approach; Hypothesis Testing; Green Swan; Financial Stability; Annex II Countries; Financial Time Series; Kernels; Stock Index; Machine Learning; Statistical Learning; Optimization; WSAR Algorithm; Deep Neural Networks; Phyton; Parameter Estimation; COVID-19; Clustering Analyses; Artificial Neural Networks; Performance Criteria; Time Series Forecasting; Statistical Inference;
    All these keywords.

    JEL classification:

    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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