• Title/Summary/Keyword: goodness of fit test

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LOCAL INFLUENCE ON THE GOODNESS-OF-FIT TEST STATISTIC IN MAXIMUM LIKELIHOOD FACTOR ANALYSIS

  • Jung, Kang-Mo
    • Journal of applied mathematics & informatics
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    • v.5 no.2
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    • pp.489-498
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    • 1998
  • The influence of observations the on the goodness-of-fit test in maximum likelihood factor analysis is investigated by using the local influence method. under an appropriate perturbation the test statistic forms a surface. One of main diagnostics is the maximum slope of the perturbed surface the other is the direction vector cor-responding to the curvature. These influence measures provide the information about jointly influence measures provide the information about jointly influential observations as well as individ-ually influential observations.

Bootstrap Method for Row and Column Effects Model

  • Jeong, Hyeong-Chul
    • Communications for Statistical Applications and Methods
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    • v.12 no.2
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    • pp.521-529
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    • 2005
  • In this paper, we consider a bootstrap method to the 'row and column effects model' (RC model) to analyze a contingency table with ordered variables. We propose a bootstrap procedure for testing of independence, equality of intervals, and goodness of fit in the RC model. A real data example is included.

Test for the Pareto Distribution Based on the Transformed Sample Lorenz Curve

  • Kang, Suk-Bok;Cho, Young-Suk
    • Proceedings of the Korean Statistical Society Conference
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    • 2002.05a
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    • pp.133-137
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    • 2002
  • A powerful and easily computed goodness-of-fit test for Pareto distribution which does not depend on the unknown location and scale parameters is proposed based on the transformed sample Lorenz curve. We compare the power of the proposed test statistic with the other goodness-of-fit tests for Pareto distribution against various alternatives through Monte Carlo methods.

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A Study on Distribution Based on the Normalized Sample Lorenz Curve

  • Suk-Bok kang;Cho, Young-Suk
    • Communications for Statistical Applications and Methods
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    • v.8 no.1
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    • pp.185-192
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    • 2001
  • Using the Lorenz curve that is proved to be a powerful tool to measure the income inequality within a population of income receivers, we propose the normalized sample Lorenz curve for the goodness-of-fit test that is very important test in statistical analysis. For two hodgkin's disease data sets, we compare the Q-Q plot and the proposed normalized sample Lorenz curve.

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Goodness-of-fit Test for the Weibull Distribution Based on Multiply Type-II Censored Samples

  • Kang, Suk-Bok;Han, Jun-Tae
    • Communications for Statistical Applications and Methods
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    • v.16 no.2
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    • pp.349-361
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    • 2009
  • In this paper, we derive the approximate maximum likelihood estimators of the shape parameter and the scale parameter in a Weibull distribution under multiply Type-II censoring by the approximate maximum likelihood estimation method. We develop three modified empirical distribution function type tests for the Weibull distribution based on multiply Type-II censored samples. We also propose modified normalized sample Lorenz curve plot and new test statistic.

Comparison of Goodness-of-Fit Tests using Grouping Strategies for Multinomial Logit Regression Model (다항 로짓 회귀모형에서의 그룹화 전략을 이용한 적합도 검정 방법 비교)

  • Song, Mi Kyung;Jung, Inkyung
    • The Korean Journal of Applied Statistics
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    • v.26 no.6
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    • pp.889-902
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    • 2013
  • Several goodness-of-fit test statistics have been proposed for a multinomial logit regression model; however, the properties of the proposed tests were not adequately studied. This paper evaluates three different goodness-of-fit tests using grouping strategies, proposed by Fagerland et al. (2008), Bull (1994), and Pigeon and Heyse (1999). In addition, Pearson (1900)'s method is also examined as a reference. Simulation studies were conducted to evaluate the four methods in terms of null distribution and power. A real data example is presented to illustrate the methods.

Power comparison of distribution-free two sample goodness-of-fit tests (이표본 분포 동일성에 대한 분포무관 검정법 간 검정력 비교 연구)

  • Kim, Seon Bin;Lee, Jae Won
    • The Korean Journal of Applied Statistics
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    • v.30 no.4
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    • pp.513-528
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    • 2017
  • Statistics are often used to test two samples if they have been drawn from the same underlying distribution. In this paper, we introduce several well-known distribution-free tests to compare distributions and conduct an extensive Monte-Carlo simulation to specify their behaviors. We consider various circumstances of when two distributions vary in (1) location, (2) scale, (3) symmetry, (4) kurtosis, (5) tail weight. A practical guideline for two-sample goodness-of-fit test is presented based on the simulation result.

A Study On Variance Estimation in Smoothing Goodness-of-Fit Tests (평활 적합도 검정에서의 분산추정의 영향)

  • Yoon, Yong-Hwa;Kim, Jong-Tae;Lee, Woo-Dong
    • Journal of the Korean Data and Information Science Society
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    • v.9 no.2
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    • pp.189-202
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    • 1998
  • The goat of this paper is to study on variance estimation - Rice variance estimation, Gasser, Sroka and Jennen-Steinmetz's varince estimation - in smoothing goodness-of-fit tests. The comparisons of powers on test statistics are conducted by the change of variance, the number of oscillations, the amplitude of the alternative sample distribution.

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A Goodness-Of-Fit Test for Adaptive Fourier Model in Time Series Data

  • Lee, Hoonja
    • Communications for Statistical Applications and Methods
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    • v.10 no.3
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    • pp.955-969
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    • 2003
  • The classical Fourier analysis, which is the typical frequency domain approach, is used to detect periodic trends that are of the sinusoidal shape in time series data. In this article, using a sequence of periodic step functions, describes an adaptive Fourier series where the patterns may take general periodic shapes that include sinusoidal as a special case. The results, which extend both Fourier analysis and Walsh-Fourier analysis, are applies to investigate the shape of the periodic component. Through the real data, compare the goodness-of-fit of the model using two methods, the adaptive Fourier method which is proposed method in this paper and classical Fourier method.