Finding the MLE for a Given Probability Using iid PDF

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Homework Help Overview

The problem involves finding the maximum likelihood estimate (MLE) for the probability P(X<2) given a probability density function (PDF) for independent and identically distributed (iid) random variables. The subject area is statistics, specifically focusing on MLE and probability calculations.

Discussion Character

  • Exploratory, Mathematical reasoning

Approaches and Questions Raised

  • Participants discuss the relationship between the MLE of the parameter theta and the probability P(X<2). There is an attempt to express P(X<2) in terms of the sample mean, \overline{X}, and some participants suggest using the integral of the PDF instead of a direct calculation.

Discussion Status

The discussion is ongoing, with participants exploring different formulations of the probability and clarifying the use of the PDF. Some guidance has been offered regarding the expression for P(X<2), but no consensus has been reached on the correct approach.

Contextual Notes

Participants are working under the constraints of the given PDF and the requirement to find the MLE without additional information about the sample size or specific values of X.

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Homework Statement



Suppose X1...Xn are iid and have PDF [tex]f(x; \theta) = \frac{1}{\theta} e^{\frac{-x}{\theta}} \ \ \ 0<x<\infty[/tex]

Find the MLE of P(X<2).

Homework Equations





The Attempt at a Solution



I know the MLE of theta is [tex]\overline{X}[/tex]

so would [tex]P(X<2) = 1 - \frac{1}{\overline{X}} e^{\frac{-2}{\overline{X}}}[/tex]?

Thank you in advance.
 
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nope, i think you should use the integral of pdf. the pdf is like the puntual probability of value x.
 
you mean:

[tex]1 - e^{\frac{-2}{\overline{X}}}[/tex]
 
correct, i think
 
Thanks.
 

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