expinv - mu from a set of data, you can get a more accurate...

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expinv Exponential inverse cumulative distribution function Syntax X = expinv(P,mu) [X,XLO,XUP] = expinv(X,mu,pcov,alpha) Description X = expinv(P,mu) computes the inverse of the exponential cdf with parameters specified by mean parameter mu for the corresponding probabilities in P . P and mu can be vectors, matrices, or multidimensional arrays that all have the same size. A scalar input is expanded to a constant array with the same dimensions as the other input. The parameters in mu must be positive and the values in P must lie on the interval [0 1]. [X,XLO,XUP] = expinv(X,mu,pcov,alpha) produces confidence bounds for X when the input mean parameter mu is an estimate. pcov is the variance of the estimated mu . alpha specifies 100(1 - alpha )% confidence bounds. The default value of alpha is 0.05. XLO and XUP are arrays of the same size as X containing the lower and upper confidence bounds. The bounds are based on a normal approximation for the distribution of the log of the estimate of mu . If you estimate
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Unformatted text preview: mu from a set of data, you can get a more accurate set of bounds by applying expfit to the data to get a confidence interval for mu , and then evaluating expinv at the lower and upper end points of that interval. The inverse of the exponential cdf is The result, x , is the value such that an observation from an exponential distribution with parameter will fall in the range [0 x ] with probability p . Examples Let the lifetime of light bulbs be exponentially distributed with = 700 hours. What is the median lifetime of a bulb? expinv(0.50,700) ans = 485.2030 Suppose you buy a box of "700 hour" light bulbs. If 700 hours is the mean life of the bulbs, half of them will burn out in less than 500 hours. See Also expcdf | expfit | explike | exppdf | exprnd | expstat | icdf How To Exponential Distribution Provide feedback about this page expfit explike 1984-2009 The MathWorks, Inc. Terms of Use Patents Trademarks Acknowledgments...
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This note was uploaded on 11/29/2010 for the course ECE 302 taught by Professor Gelfand during the Spring '08 term at Purdue University-West Lafayette.

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expinv - mu from a set of data, you can get a more accurate...

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