{"id":569,"date":"2017-09-28T03:51:44","date_gmt":"2017-09-28T03:51:44","guid":{"rendered":"http:\/\/jsr.isrt.ac.bd\/?post_type=article&p=569"},"modified":"2017-09-28T03:53:28","modified_gmt":"2017-09-28T03:53:28","slug":"comparative-study-accuracy-chi-squared-approximation-power-divergence-statistic-pearsons-chi-squared-statistic-sparse-contingency-tables","status":"publish","type":"article","link":"http:\/\/jsr.isrt.ac.bd\/article\/comparative-study-accuracy-chi-squared-approximation-power-divergence-statistic-pearsons-chi-squared-statistic-sparse-contingency-tables\/","title":{"rendered":"A comparative study of the accuracy of the chi-squared approximation for the power-divergence statistic and Pearson’s chi-squared statistic in sparse contingency tables"},"content":{"rendered":"
The Power divergence family of statistics was introduced by Cressie and Read
\nin 1984. The likelihood ratio statistic and the Pearson\u2019s chi-squared statistic are
\nexamples of the many members of the power divergency family which are linked
\nthrough a family parameter . We present here the results of a comparative simulation
\nstudy on the accuracy of the chi-squared approximation for two members
\nof the family ( and )\u00a0when they are used for goodness-of-fit testing in sparse contingency tables.<\/p>\n