What is the minimum variance unbiased estimator for the population mean?

What is the minimum variance unbiased estimator for the population mean?

What is the minimum variance unbiased estimator for the population mean?

In statistics a minimum-variance unbiased estimator (MVUE) or uniformly minimum-variance unbiased estimator (UMVUE) is an unbiased estimator that has lower variance than any other unbiased estimator for all possible values of the parameter.

How do you find the variance of an unbiased estimator?

Thus, the variance itself is the mean of the random variable Y=(X−μ)2. This suggests the following estimator for the variance ˆσ2=1nn∑k=1(Xk−μ)2. By linearity of expectation, ˆσ2 is an unbiased estimator of σ2.

What is unbiased estimator of variance?

A statistic d is called an unbiased estimator for a function of the parameter g(θ) provided that for every choice of θ, Eθd(X) = g(θ). Any estimator that not unbiased is called biased. The bias is the difference bd(θ) = Eθd(X) − g(θ). We can assess the quality of an estimator by computing its mean square error.

What does minimum variance mean?

Definition: A minimum variance portfolio indicates a well-diversified portfolio that consists of individually risky assets, which are hedged when traded together, resulting in the lowest possible risk for the rate of expected return.

Is the minimum variance unbiased estimator consistent?

If σ2 is the variance of each block-specific ˜θ then the variance of the average is σ2/[n/n0], which goes to zero as n→∞. So there is a consistent unbiased estimator and so the MVUE is also consistent.

What is minimum variance?

DEFINITION. A minimum variance portfolio is an investing method that helps you maximize returns and minimize risk. It involves diversifying your holdings to reduce volatility, or such that investments that may be risky on their own balance each other out when held together.

How do you calculate unbiased estimates?

Unbiased Estimator

  1. Draw one random sample; compute the value of S based on that sample.
  2. Draw another random sample of the same size, independently of the first one; compute the value of S based on this sample.
  3. Repeat the step above as many times as you can.
  4. You will now have lots of observed values of S.

Is sample variance an unbiased estimator?

A proof that the sample variance (with n-1 in the denominator) is an unbiased estimator of the population variance.

Why is the minimum variance portfolio important?

A minimum variance portfolio holds individual, volatile securities that aren’t correlated with one another. One security might be surging in value while another is plummeting, it doesn’t matter. Because of their low correlation, the portfolio as a whole is viewed as less risky.

What is minimum variance unbiased estimator?

The estimator described above is called minimum-variance unbiased estimator (MVUE) since, the estimates are unbiased as well as they have minimum variance. Sometimes there may not exist any MVUE for a given scenario or set of data.

Which minimizes the mean squared error among unbiased estimators?

Since the mean squared error (MSE) of an estimator δ is the MVUE minimizes MSE among unbiased estimators. In some cases biased estimators have lower MSE because they have a smaller variance than does any unbiased estimator; see estimator bias .

Does the MVUE minimize MSE among unbiased estimators?

the MVUE minimizes MSE among unbiased estimators. In some cases biased estimators have lower MSE because they have a smaller variance than does any unbiased estimator; see estimator bias.

What is the MSE of a biased estimator?

Since the mean squared error (MSE) of an estimator δ is the MVUE minimizes MSE among unbiased estimators. In some cases biased estimators have lower MSE because they have a smaller variance than does any unbiased estimator; see estimator bias . .