• Title/Summary/Keyword: Goodness

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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.

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.

On scaled cumulative residual Kullback-Leibler information

  • Hwang, Insung;Park, Sangun
    • Journal of the Korean Data and Information Science Society
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    • v.24 no.6
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    • pp.1497-1501
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    • 2013
  • Cumulative residual Kullback-Leibler (CRKL) information is well defined on the empirical distribution function (EDF) and allows us to construct a EDF-based goodness of t test statistic. However, we need to consider a scaled CRKL because CRKL is not scale invariant. In this paper, we consider several criterions for estimating the scale parameter in the scale CRKL and compare the performances of the estimated CRKL in terms of both power and unbiasedness.

Testing the Goodness of Fit of a Parametric Model via Smoothing Parameter Estimate

  • Kim, Choongrak
    • Journal of the Korean Statistical Society
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    • v.30 no.4
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    • pp.645-660
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    • 2001
  • In this paper we propose a goodness-of-fit test statistic for testing the (null) parametric model versus the (alternative) nonparametric model. Most of existing nonparametric test statistics are based on the residuals which are obtained by regressing the data to a parametric model. Our test is based on the bootstrap estimator of the probability that the smoothing parameter estimator is infinite when fitting residuals to cubic smoothing spline. Power performance of this test is investigated and is compared with many other tests. Illustrative examples based on real data sets are given.

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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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Testing Uniformity Based on Regression and EDF

  • Kim, Nam-Hyun
    • Communications for Statistical Applications and Methods
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    • v.14 no.3
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    • pp.623-632
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    • 2007
  • Some tests of the goodness of fit of the uniform distribution between 0 and 1 are presented. The powers of the tests under certain alternatives are examined. As a result, the statistic based on the difference between the order statistics and the modal value of them gives good powers. We also give modifications of the statistic without using the extensive tables of the critical points.

Quantiles for Shapiro-Francia W' Statistic

  • Rahman, Mezbahur;Ali, Mir Masoom
    • Journal of the Korean Data and Information Science Society
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    • v.10 no.1
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    • pp.1-10
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    • 1999
  • Table of the empirical quantiles for the well known Shapiro-Francia W' goodness of fit statistic is produced which is more accurate than the existing ones. Prediction equation for the quantiles of W' statistic for sample sizes 30 or more we developed. The process of computing the expected values for the standard normal variate is discussed. This work is intended to make the Shapiro-Francia W' statistic more accessible to the practitioner.

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

  • Kang, Suk-Bok;Cho, Young-Seuk;Han, Jun-Tae
    • Journal of the Korean Data and Information Science Society
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    • v.19 no.4
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    • pp.1441-1448
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    • 2008
  • We propose the modified quantile-quantile (Q-Q) plot using the approximate maximum likelihood estimators and the modified normalized sample Lorenz curve (NSLC) plot for the extreme value distribution based on multiply Type-II censored samples. Using two example data sets, we picture the modified Q-Q plot and the modified NSLC plot.

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Likelihood ratio in estimating Chi-square parameter

  • Rahman, Mezbahur
    • Journal of the Korean Data and Information Science Society
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    • v.20 no.3
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    • pp.587-592
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    • 2009
  • The most frequent use of the chi-square distribution is in the area of goodness-of-t of a distribution. The likelihood ratio test is a commonly used test statistic as the maximum likelihood estimate in statistical inferences. The recently revised versions of the likelihood ratio test statistics are used in estimating the parameter in the chi-square distribution. The estimates are compared with the commonly used method of moments and the maximum likelihood estimate.

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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.