Sentence examples for formula of the probability from inspiring English sources

The formula of the probability confidence is as follows: p=left{begin{array}{c}1 f(x)/2+0.5 0end{array}kern0.5em begin{array}{c}f(x ge 1 -1<f(x)<1 f(x le -1end{array}right.

There are some limitations in the method that based on the definition of the predicting parameters in the probability integral method and the field measured data to calculate subsidence parameters, while the Origin software has a strong user-defined function, the predicting parameters are obtained via combining theoretical formula of the probability integral method.

When there are several possible ways (bi- or multi-furcations) to transmit the signal from the input node to the output node (linear sub-pathways), the formula of the probability of the union of several events can be used.

As a special case, when only the first two moments of response are considered, an analytical formula for the probability of failure is also proposed.

Then, we need to develop a mathematical formula for the probability of concordant enrichment score (CES) of a given gene set S that contains m S genes: which can be useful for prioritizing different gene sets in practice.

For example, it provides a formula for the probability of obtaining 10 sixes in 50 rolls of a die.

The formula for the probability of resistance for any fitness value and the expected number of resistant cells is derived in Iwasa et al, 2006.

A closed form formula for the probability of PDCG is difficult to obtain, so we evaluate it numerically by generating 107 different values for each channel gain element and calculating the average number of times at which neither primary user satisfies (101) at a given P1 and P2; then by subtracting it from 1, we get a numerical estimate for the probability of PDCG.

For this method we derive a formula for the probability of finding the correct model, provided the data set used satisfies an optimality criterion.

For this method we derived a formula for the probability of finding the correct model, provided the data set used is optimal.

In this paper, we introduce a scale-free structure prior for graphical models based on the formula for the probability of a network under a simple scale-free network model.