Sentence examples for predictor process from inspiring English sources

We consider the recent history functional linear models, relating a longitudinal response to a longitudinal predictor where the predictor process only in a sliding window into the recent past has an effect on the response value at the current time.

The measure is based on linear vector autoregressive (VAR) modelling: suppose that the (again, possibly multivariate) "predictee" process X t is modelled as a vector linear regression on its own past, as well as on the past of the "predictor" process Y t : X t = A 1 X t − 1 + A 2 X t − 2 + … + B 1 Y t − 1 + B 2 Y t − 2 + … + ε t (8).

The finite sample properties of the proposed estimation algorithm are studied under various lag structures and correlation levels among the predictor processes in simulation studies.

Multiple regression will be used to determine the relationship between predictors, process measures and outcome.

However, both approaches have serious drawbacks—for example, the predictor selection process may not be stable (small changes in the data or in the predictor selection process could lead to different predictors being included in the final model).

We examined the influence of changing two critical components, feature selection and classification algorithm in the predictor development process, for three different prediction problems that represented three levels of difficulty in a clinically annotated human breast cancer data set.

Migration beyond the western park boundary was less influenced by these predictors and process model performance suggested an important control on recent migrations was excluded.

In this paper, a novel periodic disturbance rejection controller is designed based on the Smith predictor platform for process with long dead-time.

The method is illustrated via the application to a non-linear single-input single-output reactor, where a Takagi Sugeno model serves as a predictor of the process future behavior.

The paper presents a new modified Smith predictor (MSP) for processes with a long time delay.

The algorithm systematically chooses the process predictors by using a particular selection criterion, namely the coefficient of determination (or R-squared).