4. [Limit Theorems] Suppose there is a random sample of n calendar days and for each day we observe the number of purchase orders recieved by an online market, {x1, x2, , ..., xn}. Assume that the number of orders follows the Poisson distribution with the daily intensity parameter A. (a) Suggest a consistent estimator  for the unobserved parameter A. (b) Using the Central Limit Theorem, derive the asymptotic distribution of  as n → ∞o. (c) Can you suggest a transformation g(Â) for this estimator such that the asymptotic distribution does not depend on the latent parameter \?

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4. [Limit Theorems] Suppose there is a random sample of n calendar days and for each day we observe
the number of purchase orders recieved by an online market, {x1, x2, , ..., xn}. Assume that the number
of orders follows the Poisson distribution with the daily intensity parameter A.
(a) Suggest a consistent estimator  for the unobserved parameter A.
(b) Using the Central Limit Theorem, derive the asymptotic distribution of  as n → ∞o.
(c) Can you suggest a transformation g(Â) for this estimator such that the asymptotic distribution
does not depend on the latent parameter \?
Transcribed Image Text:4. [Limit Theorems] Suppose there is a random sample of n calendar days and for each day we observe the number of purchase orders recieved by an online market, {x1, x2, , ..., xn}. Assume that the number of orders follows the Poisson distribution with the daily intensity parameter A. (a) Suggest a consistent estimator  for the unobserved parameter A. (b) Using the Central Limit Theorem, derive the asymptotic distribution of  as n → ∞o. (c) Can you suggest a transformation g(Â) for this estimator such that the asymptotic distribution does not depend on the latent parameter \?
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