The commonly used models of order statistics, such as the extreme values (X_{n(1)}) and (X_{n(n)}), the median, the sample range and the linear functions of order statistics are extensively studied and widely used in many fields.
Using the knowledge of order statistics, the PDF γ 1 k for k th weakest subcarrier can be expressed as [13] f γ 1 k w = ∑ i = 0 k − 1 α i λ 1 e − ρ i γ. (3).
Using the theory of order statistics [20], the selection of the maximum and the second largest is not independent, we therefore can find the joint distribution of the two largest values as f ( x, y ) = N ( N − 1 ) F ( y ) N − 2 f ( x ) f ( y ), (10).
where γ ~ m = γ BS | h BS, m | 2 Z Z + V where V = γ RS | h l ⋆, m | 2. Using the theory of order statistics, the PDF of Z can be obtained as f Z ( z ) = ∑ l = 1 L ( − 1 ) l − 1 L l exp ( − zlD ) where D = 1 γ Ω BS,R + 1 γ RS Ω R,B.
Specifically, the BALF data were normalized Using a linear combination of order statistics to determine a subset of peptides [ 23] followed by mean centering, and the plasma data were normalized using a rank invariant peptide subset [ 21] followed by median centering.
To overcome difficulties of PORFDC, stochastic FDC was used based on the principle of order statistics.
Next, we used the joint cumulative distribution of order statistics to evaluate the probability of observing a particular configuration of ranks across different organisms by chance [ 19].
The first proposal used the joint PDF of a subset of order statistics, and has been proposed by Jones and Larsen (2004).
Based on the common structure, we then derive the marginal distributions of the ordered eigenvalues, using a classical result from the theory of order statistics, along with the multilinear property of the determinant.
Since the entropy estimators are functions of order statistics, then the entropy estimation using RSS and DRSS involves ordering the RSS units.
Who here has heard of order statistics?
