The other is to specify the distribution using the mean of the lognormal distribution itself and a term called the ‘error factor’. One is to specify the mean and standard deviation of the underlying normal distribution (mu and sigma) as described above. Lognormal distributions are typically specified in one of two ways throughout the literature. A lognormal distribution is defined by a density function of f (y) = EXP( - ((LOG(y) – mu)^2) / (2 * sigma^2) ) / (y * sigma * SQR(2 * pi)), for y > 0 DefinitionĪ random variable X is said to follow a lognormal distribution if the random variable Y = log ( X ) is normally distributed, N ( mu, sigma^2 ). Many people from the RISKANAL list responded to my request (see the list below many thanks, all of you) with a wealth of specific and general information. I had a lognormal distribution defined in terms of its mean and 95-percentile values, and I needed help in determining its standard deviation. I was stuck in a distant part of Papua New Guinea some years ago without reference sources. Techniques and special applications Introduction
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