Maximum likelihood estimator

I need to maximize L. I tried with taking the [math]\ln(L(\theta))[/math] but when it comes to a discrete distribution I get a little confused. I dont need hints I need the solution as for continuous distributions I don't have problems. Thanks anyway though
 
We don’t provide the solution here, only hints.
Hint: let [imath]p=\frac{1}{\theta}[/imath]
Do you recognize the distribution after the substitution?
Post your work and explain why you're stuck?
 
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userch said:
I dont, what is the distribution?
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Well, how many discrete distributions do you know that only has one parameter? Can't be more than 5.
[math](1-p)^{x-1}p \quad; x=1,2,3,\dots[/math]
 
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Okay thx, I solved it as geometric distribution. Could lead with that in future references, it's pointless to not tell something if you know it ;) Have a good one
 
userch said:
, it's pointless to not tell something if you know it
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The point is for you to figure it out on your own and you did. ;)
Make sure you convert back in terms of [imath]\theta[/imath], not p.
 
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