Description Usage Arguments Details Value Examples
View source: R/moezipfR.mean.R
Computes the expected value of the MOEZipf distribution for given values of parameters α and β.
1 | moezipfR.mean(alpha, beta, tolerance = 10^(-4))
|
alpha |
Value of the α parameter (α > 2). |
beta |
Value of the β parameter (β > 0). |
tolerance |
Tolerance used in the calculations (default = 10^{-4}). |
The expected value of the MOEZipf distribution only exists for α values strictly greater than 2. In this case, if Y is a random variable that follows a MOEZipf distribution with parameters α and β, the expected value is computed as:
E(Y) = ∑_{x = 1} ^∞ \frac{β ζ(α) x^{-α + 1}}{[ζ(α) - \bar{β}ζ(α, x)][ζ(α) - \bar{β}ζ(α, x + 1)]}\,, α > 2\,, β > 0
The mean is computed calculating the partial sums of the serie, and it stops when two
consecutive partial sums differs less than the tolerance
value.
The last partial sum is returned.
A positive real value corresponding to the mean value of the distribution.
1 2 | moezipfR.mean(2.5, 1.3)
moezipfR.mean(2.5, 1.3, 10^(-3))
|
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