Search results
Results from the WOW.Com Content Network
Thus, the geometric mean provides a summary of the samples whose exponent best matches the exponents of the samples (in the least squares sense). In computer implementations, naïvely multiplying many numbers together can cause arithmetic overflow or underflow. Calculating the geometric mean using logarithms is one way to avoid this problem.
The mean of the geometric distribution is its expected value which ... Fisher Information is calculated as the negative expected value of the second derivative: = ...
Negative-hypergeometric distribution (like the hypergeometric distribution) deals with draws without replacement, so that the probability of success is different in each draw. In contrast, negative-binomial distribution (like the binomial distribution) deals with draws with replacement , so that the probability of success is the same and the ...
The arithmetic mean, or less precisely the average, of a list of n numbers x 1, x 2, . . . , x n is the sum of the numbers divided by n: + + +. The geometric mean is similar, except that it is only defined for a list of nonnegative real numbers, and uses multiplication and a root in place of addition and division:
A power mean serves a non-linear moving average which is shifted towards small signal values for small p and emphasizes big signal values for big p. Given an efficient implementation of a moving arithmetic mean called smooth one can implement a moving power mean according to the following Haskell code.
Nomograms to graphically calculate arithmetic (1), geometric (2) and harmonic (3) means, z of x=40 and y=10 (red), and x=45 and y=5 (blue) Of all pairs of different natural numbers of the form ( a , b ) such that a < b , the smallest (as defined by least value of a + b ) for which the arithmetic, geometric and harmonic means are all also ...
The second form above illustrates that the logarithm of the geometric mean is the weighted arithmetic mean of the logarithms of the individual values. If all the weights are equal, the weighted geometric mean simplifies to the ordinary unweighted geometric mean. [1]
The sum of independent negative-binomially distributed random variables r 1 and r 2 with the same value for parameter p is negative-binomially distributed with the same p but with r-value r 1 + r 2. The negative binomial distribution is infinitely divisible, i.e., if Y has a negative binomial distribution, then for any positive integer n, there ...