• Journal of Integrative Natural Science
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• v.7 no.2
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• pp.138-144
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• 2014

Fisher information matrix plays an important role in statistical inference of unknown parameters. Especially, it is used in objective Bayesian inference where we calculate the posterior distribution using a noninformative prior distribution, and also in an example of metric functions in geometry. To estimate parameters in a distribution, we can use the Fisher information matrix. The more the number of parameters increases, the more its matrix form gets complicated. In this paper, by using Mathematica programs we derive the Fisher information matrix for 4-parameter generalized gamma distribution which is used in reliability theory.

• Journal of Korea Water Resources Association
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• v.42 no.4
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• pp.331-341
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• 2009

In this study, we compared the observed information matrix with the Fisher information matrix to estimate the uncertainty of maximum likelihood estimators of the generalized logistic (GL) distribution. The previous literatures recommended the use of the observed information matrix because this is convenient since this matrix is determined as the part of the parameter estimation procedure and there is little difference in accuracy between the observed information matrix and the Fisher information matrix for large sample size. The observed information matrix has been applied for the generalized logistic distribution based on the previous study without verification. For this purpose, a simulation experiment was performed to verify which matrix gave the better accuracy for the GL model. The simulation results showed that the variance-covariance of the ML parameters for the GL distribution came up with similar results to those of previous literature, but it is preferable to use of the Fisher information matrix to estimate the uncertainty of quantile of ML estimators.

• Journal of the Korean Data and Information Science Society
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• v.20 no.1
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• pp.39-48
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• 2009

Fisher information matrix plays an important role in statistical inference of unknown parameters. Especially, it is used in objective Bayesian inference which derives to the posterior distribution using a noninformative prior distribution and is an example of metric functions in geometry. The more parameters for estimating in a distribution are, the more complicate derivation of the Fisher information matrix for the distribution is. In this paper, we derive to the Fisher information matrix for 3-parameters Weibull distribution which is used in reliability theory using Mathematica programs.

• Honam Mathematical Journal
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• v.35 no.1
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• pp.29-35
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• 2013

The Fisher information matrix plays a significant role i statistical inference in connection with estimation and properties of variance of estimators. Using Bivariate Lomax distribution, we can define "statistical model" and drive the Fisher information matrix of Bivariate Lomax distribution. In this paper, we correct the wrong of the paper [7].

• The Journal of Industrial Distribution & Business
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• v.9 no.7
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• pp.33-42
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• 2018

Purpose - This paper aims to verify whether the Fisher effect and the international Fisher effect are significant between China and South Korea in the long and short run, respectively. Research design, data, and methodology - The annual and monthly data, respectively, are employed to conduct an empirical estimation under the fully modified ordinary least squares(FMOLS). The nominal interest rate is treated as an independent variable. The inflation rate is treated as a dependent variable. Results - The results exhibit whenever in the long or short run, the Fisher effect exists in China and South Korea. However, the Fisher effect in South Korea is more significant than that of in China. Meanwhile, an empirical analysis is also preformed to investigate the long-run and the short-run international Fisher effect between China and South Korea. The deviation from the equilibrium relationship is that the commodity market and the Financial market have started to integrate in China. But China's integrated level proved to be relatively lower. Conclusions - To exploit that the Fisher effect and the international Fisher effect hold between China and South Korea can help both countries deal with the sufferings from integration of the commodity market and the financial market.

• Honam Mathematical Journal
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• v.29 no.1
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• pp.75-81
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• 2007

The Fisher information matrix plays a significant role in statistical inference in connection with estimation and properties of variance of estimators. In this paper, the parameter space of the normal distribution using its Fisher's matrix is defined. The Riemannian curvature and J-divergence to parameter space are calculated.

• Journal of the Korean Data and Information Science Society
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• v.21 no.3
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• pp.575-580
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• 2010

The Fisher information matrix plays a significant role in statistical inference in connection with estimation and properties of variance of estimators. In this paper, the parameter space of the t-distribution using its Fisher's matrix is de ned. The ${\alpha}$-scalar curvatures to parameter space are calculated.

• Honam Mathematical Journal
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• v.28 no.3
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• pp.433-438
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• 2006

The Fisher information matrix plays a significant role in statistical inference in connection with estimation and properties of variance of estimators. In this paper, the parameter space of the t-distribution using its Fisher's matrix is defined. The Riemannian and scalar curvatures to parameter space are calculated.

• Proceedings of the Safety Management and Science Conference
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• 2008.04a
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• pp.451-460
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• 2008

This paper reviews nonparametric statistics by Neyman-Pearson test and Fisher test. Nonparametric statistics deal with the small sample with distribution-free assumption in multi-product and small-volume production. Two tests for various nonparametric statistic methods such as sign test, Wilcoxon test, Mann-Whitney test, Kruskal-Wallis test, Mood test, Friedman test and run test are also presented with the steps for testing hypotheses and test of significance.

• Communications for Statistical Applications and Methods
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• v.23 no.4
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• pp.321-334
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• 2016

In this paper, we propose power t distribution based on t distribution. We also study the properties of and inferences for power t model in order to solve the problem of real data showing both skewness and heavy tails. The comparison of skew t and power t distributions is based on density plots, skewness and kurtosis. Note that, at the given degree of freedom, the kurtosis's range of the power t model surpasses that of the skew t model at all times. We draw inferences for two parameters of the power t distribution and four parameters of the location-scale extension of power t distribution via maximum likelihood. The Fisher information matrix derived is nonsingular on the whole parametric space; in addition we obtain the profile log-likelihood functions on two parameters. The response plots for different sample sizes provide strong evidence for the estimators' existence and unicity. An application of the power t distribution suggests that the model can be very useful for real data.