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Parameter Estimation and Evaluation Maximum Likelihood Estimation Maximum Likelihood Estimation Remarks: The likelihood function L(x")is algebraically equal to the joint PDF or PMF of the random sample X"when Xn=xn. The conceptual difference between them is that the like- lihood L(x")is a function of 0,with x"held fixed. Given 0,the likelihood L(x")is a measure of the prob- ability or probability density with which the observed sample x"will occur. The joint PDF/PMF of the random sample X",fxm(x",0), is different from the population distribution f(x,0).The latter is the PDF/PMF of each random variable Xi. Parameter Estimation and Evaluation Introduction to Statistics and Econometrics April 21,2020 19/207Parameter Estimation and Evaluation Parameter Estimation and Evaluation Introduction to Statistics and Econometrics April 21, 2020 19/207 Maximum Likelihood Estimation Maximum Likelihood Estimation Remarks:
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