Sentence examples for a pair of observed from inspiring English sources

If both criteria hold for a pair of observed classes, the position of the mode in the feature space is recalculated as follows: let N i and N j denote the number of pixels in clusters i and j respectively, and let us suppose that the two are merged into cluster k.

For a given pair of observed and predicted data values, is considered to have a possible range of values described by a normal distribution, with a mean of and a SD given by the estimate of sigma (see Table 1 ).

Second, we examined the root mean square (RMS) difference, summed over all pairs of observed haplotypes, between the separation of the pair in one tree and their separation in the other.

To do this, we obtained maximum-likelihood estimates of the genotypes TT, TC and CC for each of a pair of parents, given the observed genotypes in the family.

Then, the marginal distribution of the observed number of alleles is beta-binomial (e.g., Casella & George 1992; Sorensen & Gianola 2002), that is, the probability of observing copies among the 2 N alleles scored is (17) Consider now a pair of loci, and let the observed number of copies of the four alleles be represented as haplotype frequencies are not relevant in the model that follows.

If ( C_{eff} = 1 ), then the pair of observed and estimated data match well.

The difference between each pair of observed (e.g., Cobs) and predicted (e.g., " ") values for the dependent variables is calculated, yielding the residual (Cobs – ).

When fitting population data, predicted concentrations for each subject depend on the difference between each subject's parameters (Pi) and the population parameters (Ppop) and the difference between each pair of observed (Cobs) and predicted concentrations.

We create a link between a pair of languages i, j if the observed z-score, (z_{ij}), is above the threshold t [42].

Such method belongs to the large and well-established family of predictors that are referred to as node neighbourhood techniques (Cannistraci et al., 2013a), because to assign a likelihood score to any candidate interaction (i.e. a pair of non-connected proteins in the observed PPIN), they rely on the topological properties of the seed proteins' neighbours.

The complete class theorem states that there is always a pair of prior and loss functions, for which observed decisions are optimal in a Bayesian sense.