Mathematics, 17.02.2020 23:09 cyaransteenberg
Let Y denote a Bernoulli(θ) random variable with 0 < θ < 1. Suppose we are interested in estimating the odds ratio, γ = θ/(1 − θ), which is the probability of success over the probability of failure. Given a random sample {Y1,...,Yn}, we know that an unbiased and consistent estimator of θ is Y¯, the proportion of successes in n trials. A natural estimator of γ is G = Y¯ /(1−Y¯), the proportion of successes over the proportion of failures in the sample
a. Why is G not an unbiased estimator of γ (show this matematically and explain)?
b. Use the properties of plim (mathmatically) to show that G or Y/(1-Y) is a consistent estimator of γ.
Answers: 2
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Let Y denote a Bernoulli(θ) random variable with 0 < θ < 1. Suppose we are interested in estim...
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