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Goodness of Fit in the Marginal Modeling of Round-Trip Times for Networked Robot Sensor Transmissions. [PDF]
Sensors (Basel)Fernández-Madrigal JA +5 more
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A Scale for Older adults' decisional balance regarding physical ACTIVity (SO-ACTIV): development and validation in a French sample. [PDF]
Front Public HealthGiaufer C +5 more
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Estimating and Fitting the Non-continuous category scored Polytomous Items under the Weighted Score Logistic Model and its Simulation Study. [PDF]
Appl Psychol MeasJian X, Dai B, Qing Y, Deng Y.
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Development, validity, and reliability of the band and loop radiographic assessment scoring system (BRASS). [PDF]
Eur Oral ResChari D, Panda A, Shukla B.
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Improved Goodness-Of-Fit Tests
Biometrika, 1971Two statistics for testing goodness of fit for small sample sizes are provided. The first statistic, S, can be used to test the fit to any completely specified continuous distribution function and is more powerful than the Kolmogorov-Smirnov statistic in the cases tested.
Finkelstein, J. M., Schafer, R. E.
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Smooth Tests of Goodness of Fit
Technometrics, 1991AbstractSmooth tests of goodness of fit assess the fit of data to a given probability density function within a class of alternatives that differs ‘smoothly’ from the null model. These alternatives are characterized by their order: the greater the order the richer the class of alternatives. The order may be a specified constant, but data‐driven methods
Rayner, J. C. W., Thas, O., Best, D. J.
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2018
Based on the substitution principle, we derive one-sample goodness-of-fit tests of Kolmogorov-Smirnov and Cramer-von Mises type, respectively. In the case of a completely specified null hypothesis, these tests are distribution-free, if the cumulative distribution function under the null is a continuous function. In the case of composite null hypotheses,
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Based on the substitution principle, we derive one-sample goodness-of-fit tests of Kolmogorov-Smirnov and Cramer-von Mises type, respectively. In the case of a completely specified null hypothesis, these tests are distribution-free, if the cumulative distribution function under the null is a continuous function. In the case of composite null hypotheses,
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1998
Goodness-of-fit tests are used to validate the use of a particular distribution to describe data arising from sampling or experimentation. Numerous goodness-of-fit tests have been developed. The power divergence family of test statistics includes Pearson’s chi-squared test, the likelihood ratio test, and the Freeman-Tukey chi-squared test.
Linda J. Young, Jerry H. Young
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Goodness-of-fit tests are used to validate the use of a particular distribution to describe data arising from sampling or experimentation. Numerous goodness-of-fit tests have been developed. The power divergence family of test statistics includes Pearson’s chi-squared test, the likelihood ratio test, and the Freeman-Tukey chi-squared test.
Linda J. Young, Jerry H. Young
openaire +1 more source