goodness of fit


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goodness of fit

n
(Statistics) statistics the extent to which observed sample values of a variable approximate to values derived from a theoretical density, often measured by a chi-square test
Collins English Dictionary – Complete and Unabridged, 12th Edition 2014 © HarperCollins Publishers 1991, 1994, 1998, 2000, 2003, 2006, 2007, 2009, 2011, 2014
References in periodicals archive ?
Monte Carlo evaluations of goodness of fit indices for structural equation models.
While there are various Goodness of Fit Indexes, in application only 4 - 5 of them are in widespread use (Cengiz and Kirkbir, 2007).
Table-I illustrates, according to the literature, the lowest and highest values of the scales related to some goodness of fit14 and the goodness of fit indexes obtained from this study.
The systematic uncertainties will also influence the goodness of fit. The systematic uncertainties include the uncertainty of the center-of-mass energy determination, parametrization of the BW function, the cross section measurement, and the uncertainty of [psi](4160)'s mass and width.
In this work, we use these data to identify parameters that the model is highly insensitive to (parameters that can vary widely without affecting the goodness of fit of the model).
Table for estimating the goodness of fit of empirical distributions.
In the statistical comparison of the data mining algorithms in animal science, goodness of fit criteria have been highlighted very poorly with the exception of few researches (Grzesiak and Zaborski, 2012; Ali et al., 2015).
We study and compare the goodness of fit (GoF) performance of the proposed model with a popular test effort function based SRGM.
To examine the goodness of fit, different authors suggest indexes that reveal whether the sample data supports the theory set out, such as the chi-squared statistic ([chi square]), the GFI (goodness of fit index), the RMSEA (root mean square error of approximation), the SRMR (square root mean residual), or the AGFI (adjusted goodness of fit index).
The use of the chi-square test for goodness of fit has three assumptions: (i) observations are independent, (ii) categories are mutually exclusive, and (iii) categories are exhaustive [2].
Another approach for testing goodness of fit is Chi-square test which can be defined as: