Sentence examples for expectations of the data from inspiring English sources

Although such large networks are generally statistically significant, they do not yield directly actionable insights unless the experimentalist has specific expectations of the data.

First, that the expectations of the data subject can serve to relax informational obligations.

Each vij in the matrix V, represents the expectations of the data transmission rate between the device in network i and cloud resource j, and it takes a weighted average of the history data Vij, as shown in formula (4).

And there are two matrices V and RTT that record the expectations of the data transmission rate and the round trip time respectively, as shown in formula (2) and (3).

All three measures were correlated with one another; D and R ST, r = 0.94; D and δμ 2, r = 0.58; and R ST and δμ 2, r = 0.81; and all pairwise differences were significantly different from null expectations of the data (Additional file 9).

Two arguments were considered: First, that the expectation of the data subject could serve to relax the relevant informational obligations; second, that the technical and organisational privacy protection mechanisms provided by the biobank should serve to relax the relevant informational obligations.

This method was preferred to a kriging because the variogram or expectation of the data is unknown but the data are reliable (Cressie 1993).

To achieve this goal, we could perform gradient ascent in the log-likelihood of the training data derived from Equation (3) and incrementally adjust the weights and biases: (6) where ϵ is the learning rate, denotes an expectation of the data distribution and denotes an expectation of the distribution defined by the model.

where 〈·〉data and 〈·〉model denote expectations of the empirical data and the inner model, respectively.

Reports on the U.S. labor market, productivity, the services sector and factory orders all came in shy of expectations but the data did point to growth and recovery, albeit slower than many would hope for.

In each iteration, the expectation of the full data log-likelihood conditional on the parameters from the previous iteration, is maximized to obtain the optimal parameters for the current iteration.