Maximum Likelihood Estimation and Hypothesis Testing
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چکیده
This chapter is a brief introduction to two important statistical methods— maximum likelihood estimation and hypothesis testing. We shall show how to use these methods to test the biological sequence models developed in previous chapters against experimental data. We shall also show how hypothesis testing ideas inspire scoring methods for sequence alignment. denote the outcome of an experiment that produces n random values. A probability model for this experiment is simply a specification of the joint probability distribution of X 1 ,. .. , X n. For example, if the random variables take values in a discrete set E, a probability model is a joint probability mass function
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Maximum Likelihood Estimation and Hypothesis Testing
This chapter is a brief introduction to two important statistical methods— maximum likelihood estimation and hypothesis testing. We shall show how to use these methods to test the biological sequence models developed in previous chapters against experimental data. We shall also show how hypothesis testing ideas inspire scoring methods for sequence alignment. denote the outcome of an experiment ...
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تاریخ انتشار 2006