Question
If the magnitude of the earthquakes recorded in a region of a country follows a distribution with parameter θ
then find
i) maximum likelihood estimator of the parameter θ,
ii) maximum likelihood estimate of the parameter on the basis of the following data:
| Magnitude of the Earthquakes (on the Richter scale) |
6.7 |
7.7 |
5.6 |
7.3 |
6.7 |
6.6 |
7.8 |
6.7 |
6.2 |
5.2 |
iii) Show that maximum likelihood estimator is unbiased and sufficient for parameter θ.
Answer :
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Skip in 10
We are asked to manually find the Maximum Likelihood Estimator (MLE) for the parameter $\theta$ of an exponential distribution, then compute it for given earthquake magnitudes, and show its properties. Let's solve step by step. --- ### Given PDF of the exponential distribution: $$ f(x; \theta) = \frac{1}{\theta} e^{-x/\theta}, \quad x \ge 0, \theta > 0 $$ Data (magnitudes of earthquakes): $$ 6.7, 7.7, 5.6, 7.3, 6.7, 6.6, 7.8, 6.7, 6.2, 5.2 $$ --- ## Step i: Maximum Likelihood Estimator (MLE) of $\theta$ 1. Likelihood function For a sample $x_1, x_2, \dots, x_n$, the likelihood is: $$ L(\theta) = \prod_{i=1}^n f(x_i;\theta) = \prod_{i=1}^n \frac{1}{\theta} e^{-x_i/\theta} = \frac{1}{\theta^n} e^{-\sum x_i / \theta} $$
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