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Fugacity and BCF relate to each other in the following equation: = [6] where Z Fish is equal to the Fugacity capacity of a chemical in the fish, P Fish is equal to the density of the fish (mass/length 3), BCF is the partition coefficient between the fish and the water (length 3 /mass) and H is equal to the Henry's law constant (Length 2 /Time 2) [6]
Merton's portfolio problem. Merton's portfolio problem is a problem in continuous-time finance and in particular intertemporal portfolio choice. An investor must choose how much to consume and must allocate their wealth between stocks and a risk-free asset so as to maximize expected utility.
Girard form class is the primary expression of tree form in the United States. To allow for log trimming and a 1-foot stump height the diameter inside bark is measured at 17.3 feet above the ground. The closer the form class value to 100 the closer the log resembles a cylinder, where a value of 100 means the log is very nearly a cylinder.
This distribution for a = 0, b = 1 and c = 0.5—the mode (i.e., the peak) is exactly in the middle of the interval—corresponds to the distribution of the mean of two standard uniform variables, that is, the distribution of X = (X 1 + X 2) / 2, where X 1, X 2 are two independent random variables with standard uniform distribution in [0, 1]. [1]
Survival function. The survival function is a function that gives the probability that a patient, device, or other object of interest will survive past a certain time. [ 1] The survival function is also known as the survivor function[ 2] or reliability function. [ 3] The term reliability function is common in engineering while the term survival ...
The Weibull plot is a plot of the empirical cumulative distribution function of data on special axes in a type of Q–Q plot. The axes are versus . The reason for this change of variables is the cumulative distribution function can be linearized: which can be seen to be in the standard form of a straight line.
Exponential decay is a scalar multiple of the exponential distribution (i.e. the individual lifetime of each object is exponentially distributed), which has a well-known expected value. We can compute it here using integration by parts .
The Poisson distribution is an appropriate model if the following assumptions are true: k is the number of times an event occurs in an interval and k can take values 0, 1, 2, ... . The occurrence of one event does not affect the probability that a second event will occur. That is, events occur independently.