Results 261 to 270 of about 1,402,559 (308)

A Chi-Square Statistics Based Feature Selection Method in Text Classification

2018 IEEE 9th International Conference on Software Engineering and Service Science (ICSESS), 2018
Text classification refers to the process of automatically determining text categories based on text content in a given classification system. Text classification mainly includes several steps such as word segmentation, feature selection, weight ...
Yujia Zhai, Wei Song, Xianjun Liu, Lizhen Liu, Xinlei Zhao   +4 more
semanticscholar   +1 more source

CHI-SQUARE STATISTIC AS A SCORE TEST STATISTIC

Far East Journal of Theoretical Statistics, 2015
Summary: Chi-square test has been very successful in statistical analysis of experimental data and score test problems. In this paper, we introduce the use of score test in a generalized linear model following the theory of score test and likelihood function.
Onoghojobi, B., Olewuezi, N. P.
openaire   +2 more sources

Chi-squared statistics for KCRV candidates

Metrologia, 2005
We examine chi-squared statistics that are appropriate for analysing the adequacy of different key comparison reference value (KCRV) candidates in accounting for the observed dispersion of results of a key comparison, about the candidate estimator and within the stated uncertainty claims.
Steele, A., Douglas, R. J.
openaire   +2 more sources

Nonparametric Statistics Other Than Chi Square

1978
Prior to the preceding chapter on chi square, the great majority of the statistics we computed were parametric statistics but there was no occasion to use that expression in referring to them. These statistics frequently made assumptions (such as normality) about the nature of the population from which the samples were drawn.
Albert K. Kurtz, Samuel T. Mayo
openaire   +1 more source

A chi-square goodness-of-fit test for continuous distributions against a known alternative

Computational statistics (Zeitschrift), 2020
The chi square goodness-of-fit test is among the oldest known statistical tests, first proposed by Pearson in 1900 for the multinomial distribution. It has been in use in many fields ever since.
W. Rolke, Cristian Gutierrez Gongora
semanticscholar   +1 more source

Chi-squared statistics of association and homogeneity

International Journal of Injury Control and Safety Promotion, 2016
In the injury field, one often obtains data that are measured in categories – either on an ordinal scale (e.g., severity of injury from mild to moderate to severe) or on a nominal scale (e.g., type...
openaire   +2 more sources

Pair-difference chi-squared statistics for Key Comparisons

Metrologia, 2005
Pair-difference chi-squared statistics are useful for analysing metrological consistency within a Key Comparison. We show how they relate to classical chi-squareds and how they can be used with full rigour, for any comparison of a scalar measurand, to compare the observed dispersion of results with the dispersion that would be expected on the basis of ...
Douglas, R. J., Steele, A.
openaire   +1 more source

Chi-square Difference Tests for Comparing Nested Models: An Evaluation with Non-normal Data

, 2020
The relative fit of two nested models can be evaluated using a chi-square difference statistic. We evaluate the performance of five robust chi-square difference statistics in the context of confirmatory factor analysis with non-normal continuous outcomes.
Goran Pavlov, Dexin Shi, Albert Maydeu-Olivares   +2 more
semanticscholar   +1 more source

Relative Age Effect and chi-squared statistics

International Review for the Sociology of Sport, 2013
Traditionally, the Relative Age Effect (RAE) is determined with a chi-squared goodness-of-fit test based on a theoretical expected distribution of birthdates. This distribution must be that of the parent population, but many authors choose to replace it by a uniform distribution in order to simplify calculations.
Delorme, N., Champely, Stéphane
openaire   +2 more sources

Equivalence of Certain Chi-Squared Test Statistics

The American Statistician, 1981
Abstract In likelihood analysis of categorized data, it is well known that within a restricted class of log-linear models the likelihood kernels for multinomial and product multinomial sampling distributions are identical. In practical terms the estimation procedure for one is appropriate for the other.
Robert F. Woolson, Stephen S. Brier
openaire   +1 more source