About: Error exponents in hypothesis testing

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In statistical hypothesis testing, the error exponent of a hypothesis testing procedure is the rate at which the probabilities of Type I and Type II decay exponentially with the size of the sample used in the test. For example, if the probability of error of a test decays as , where is the sample size, the error exponent is .

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  • In statistical hypothesis testing, the error exponent of a hypothesis testing procedure is the rate at which the probabilities of Type I and Type II decay exponentially with the size of the sample used in the test. For example, if the probability of error of a test decays as , where is the sample size, the error exponent is . Formally, the error exponent of a test is defined as the limiting value of the ratio of the negative logarithm of the error probability to the sample size for large sample sizes: . Error exponents for different hypothesis tests are computed using Sanov's theorem and other results from large deviations theory. (en)
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  • In statistical hypothesis testing, the error exponent of a hypothesis testing procedure is the rate at which the probabilities of Type I and Type II decay exponentially with the size of the sample used in the test. For example, if the probability of error of a test decays as , where is the sample size, the error exponent is . (en)
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  • Error exponents in hypothesis testing (en)
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