Sentence examples for modeling the probability from inspiring English sources

A mixture of multivariate Gaussian density functions is used in modeling the probability density functions of observations in each state.

We show how future expected rate can be estimated by modeling the probability that a user will be allocated a subcarrier in a future time slot.

We show how this future expected rate can be estimated by modeling the probability that a user will be allocated a subcarrier in a future time slot.

This paper describes the first study that focuses on modeling the probability of an LNG tender car release incident due to a freight train derailment on a mainline.

By modeling the probability distribution of the instantaneous velocity in a multivariate Gaussian distribution, we demonstrated its ability to estimate mean speed with high accuracy.

Logistic regression was used for modeling the probability of abnormality of a variable in relation to the time interval before delivery.

The other two are large impact of the event and not being able to model the probability of the event.

To model the probability of an individual travelling we fitted logistic regression models to the data.

We then modelled the probability of a variable changing its position in the predictor ranking obtained in HP.

To combine multiple markers, we used a multivariate normal distribution to model the probability density function (pdf) for each class.

The first equation modelled the probability of spending.