The conventional method for testing hypotheses is to find an exact or asymptotic distributionof a test statistic. But when the model is complex and the sample size is small, difficulty often arises. Thispaper aims to ...The conventional method for testing hypotheses is to find an exact or asymptotic distributionof a test statistic. But when the model is complex and the sample size is small, difficulty often arises. Thispaper aims to present a method for finding maximum probability with the help of EM algorithm. For any fixedsample size, this method can be used not only to obtain an accurate test but also to check the real level ofa test which is build by large sample theory. Especially, while doing this, one needs neither the accurate norasymptotic distribution of the test statistic. So the method is easily performed and is especially useful for small samples.展开更多
基金This work was supported by the National Natural Science Foundation of China(Grant No.10071004).
文摘The conventional method for testing hypotheses is to find an exact or asymptotic distributionof a test statistic. But when the model is complex and the sample size is small, difficulty often arises. Thispaper aims to present a method for finding maximum probability with the help of EM algorithm. For any fixedsample size, this method can be used not only to obtain an accurate test but also to check the real level ofa test which is build by large sample theory. Especially, while doing this, one needs neither the accurate norasymptotic distribution of the test statistic. So the method is easily performed and is especially useful for small samples.