Sentence examples for I a coefficient from inspiring English sources

The model score for a generic test patient was simply: (1) s = ∑ i = 1 d   λ i   s i where d is the number of predictors in the model, s i the score associated with the ith predictor and λ i a coefficient assigned a value of 0 or 1 after comparison of the ith predictor with its corresponding cut-off point.

Thus the model score for the test patient x is obtained as follows (12) s = ∑ i = 1 d λ i s i where d is the number of predictors in the model, s i the score associated with the ith predictor and λ i a coefficient assigned a value of 0 or 1 after comparison of x i with the corresponding cut-off point.

The costs associated with inspection are assumed to be proportional to the quality of inspection: (10) C I (x ) = C i · q, where C i is a coefficient weighting the contribution of the inspection to the total costs.

Here h i represents observed heterogeneity (which may overlap with Z i ) with a coefficient of δ and w i represents unobserved heterogeneity with a coefficient of τ [38].

ψ ¯ reflects the mean tastes of the sample while ψ ˜ i is a coefficient which shows how i differs from the mean individual, and (ε is  − ε it ) is an additive disturbance assumed to be i.i.d.i.d

Basically, inclusion of escape factors causes a net reduction in Einstein's A coefficients, i.e., it modifies the atomic transition probability values.

For each cluster ((C_{m}^{delta _{i}},C_{t}^{delta _{i}})) generated by δ i, a silhouette coefficient ((gamma _{delta _{i}})) associated with the cluster is calculated reflecting its quality (line 4).

A graph is called a small world if it has (i

Linear least squares fit gave ν i = 231.8005 – 0.01869 i (THz) with a coefficient of determination of R = 0.99999998 for both OD+ and OD−.

With use of ω i, a i coefficients will calculate.

The latent evaluation score *y i is a linear function of independent variables vector x i where the i depicts individual observation, * y i = x i ′ β + ϵ i Where β is a coefficient vector, and ϵ i is the random error for the i-th individual assumed to follow a standard normal distribution.