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Geometric distribution
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===Fisher's Information (Geometric Distribution, Trials Until Success)=== Fisher information for the geometric distribution modeling the number of trials until the first success is given by: :<math>I(p) = \frac{1}{p^2(1 - p)}</math> '''Proof:''' *The '''Likelihood Function''' for a geometric random variable <math>X</math> is: :<math>L(p; X) = (1 - p)^{X - 1} p</math> *The '''Log-Likelihood Function''' is: :<math>\ln L(p; X) = (X - 1) \ln(1 - p) + \ln p</math> *The Score Function (first derivative of the log-likelihood w.r.t. <math>p</math>) is: :<math>\frac{\partial}{\partial p} \ln L(p; X) = \frac{1}{p} - \frac{X - 1}{1 - p}</math> *The second derivative of the log-likelihood function is: :<math>\frac{\partial^2}{\partial p^2} \ln L(p; X) = -\frac{1}{p^2} - \frac{X - 1}{(1 - p)^2}</math> *'''Fisher Information''' is calculated as the negative expected value of the second derivative: :<math>\begin{align} I(p) &= -E\left[\frac{\partial^2}{\partial p^2} \ln L(p; X)\right] \\ &= - \left(-\frac{1}{p^2} - \frac{1 - p}{p (1 - p)^2} \right) \\ &= \frac{1}{p^2(1 - p)} \end{align}</math>
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