The vMF correlation function proposed in (13) is expressed as a sum of terms, where each term either characterizes the scattering environment or the antenna locations.
Therefore, because of the non-diagonal structure of R − 1, the ML decoding metric (8) cannot be split in several terms, where each term is a function of only one of the constituent symbols of S1.
Hence, using y a (instead of y) to decode S1, the ML decoding metric (8) splits in L different terms, where each term is a function of only one of the constituent symbols of S0, and the COSTBC is single symbol decodable for N = 2, and M2 = 1.
Basically, a conditional hypergeometric test is performed for each GO-term where each gene is counted only in the most specific statistically significant GO-term to decorrelate and facilitate the interpretation of the results.
(1) The objective function consists of three terms, where each term refers to a worker.
However, this could be difficult and it is better to use the estimated, or empirical, information with terms where each partial derivative is evaluated at the MLEs.
Garcia-Cortes and Toro [ 20] presented a partition of the variance-covariance matrix of additive genetic values into breed-specific and breed-segregation terms, where each term is a scaled partial relationship matrix.
To investigate the relations between the GO terms characterizing the identified CDSs, we also created a network of GO terms, where each node is a GO slim annotation and two nodes are connected if they significantly share enriched combinations.
In our final model, we constructed 12 interaction terms where each of the 12 measures of structural and functional family support was interacted with the variable of parent's filial attitudes, respectively.
Selection by the LASSO method and further weight penalization by Ridge regression resulted in the final, locked algorithm, comprising 20 CAD-associated genes and 3 normalization genes in 6 meta-gene terms, where each term represents a ratio of meta-genes or meta-gene to normalization genes.
