Maximum likelihood estimator of binominal distribution

by superwolf
Tags: binominal, distribution, estimator, likelihood, maximum
superwolf is offline
May7-09, 03:19 PM
P: 193
L(x_1,...,x_n;p)=\Pi_{i=1}^{n}(\stackrel{n}{x_i}) p^{x_i}(1-p)^{n-x_i}

Correct so far?

The solution tells me to skip the [tex]\Pi[/tex]:

L(x_1,...,x_n;p)=(\stackrel{n}{x}) p^{x}(1-p)^{n-x}

This is contradictory to all the examples in my book. Why?
Phys.Org News Partner Science news on
Internet co-creator Cerf debunks 'myth' that US runs it
Astronomical forensics uncover planetary disks in Hubble archive
Solar-powered two-seat Sunseeker airplane has progress report
Defennder is offline
May8-09, 09:29 AM
HW Helper
P: 2,618
I don't understand why you wrote L(x1...xn,p). I thought the purpose was to estimate p, the probability of a designated success outcome in a Bernoulli trial. So it should be L (p) as p is the only parameter.

I also don't see any sense in omitting the multiplicative pi symbol. What is x here, anyway? x_i all refer to the observed no. of succeses of each sample size n. So what is x?

Register to reply

Related Discussions
Maximum likelihood error Calculus & Beyond Homework 1
question on maximum likelihood Set Theory, Logic, Probability, Statistics 1
Maximum likelihood Set Theory, Logic, Probability, Statistics 1
Maximum Likelihood Introductory Physics Homework 1
Maximum likelihood estimator.... Set Theory, Logic, Probability, Statistics 0