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Maximum Likelihood Estimator

  1. Mar 9, 2012 #1
    1. The problem statement, all variables and given/known data
    An observation X has density function: f(x,/theta)=6x/(t^3)*(t-x) where t is a parameter: 0<x<t.

    Given the single observation X, determine the maximum likelihood estimator for t.

    2. Relevant equations
    Included below

    3. The attempt at a solution
    For a sample size of n, the likelihood function is
    L(t)=product[6x_i/(t^3)*(t-x_i)] from i=1 to n.
    To maximize a product, we take the log L[t] and differentiate with respect to t and equate to 0.

    d/dt [Log[t]=3/t+Sum[1/(t-x_i)] for i=1 to n.
    However, I don't know how to solve 3/t+Sum[1/(t-x_i)]=0 for t since there is a t on the denominator in the sum. Is there a way to do this?

    Or have I misinterpreted the question? Since the question says, "Given a single observation X" am I not supposed to take the product over n samples but rather set n=1 when finding my likelihood function L(t)=6x_i/(t^3)*(t-x_i?
  2. jcsd
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