Introduction: The neural substrates of temporal processing are not still fully known. The majority of interval timing studies have dealt with this subject in the context of “Explicit timing” (computing the time intervals explicitly). The hypothesis “Implicit timing” (implicitly using temporal processing to improve function) has also proposed. This lesion study addressed explicit and implicit ti...

Prediction, by interval or point, of an unobserved random variable is a fundamental problem in statistics. This paper deals with constructing a prediction interval on a future observation Xr in an ordered sample of size n from an underlying distribution (under parametric uncertainty), where the first k observations X1 < X2 <  < Xk, 1k<rn, have been observed. Prediction intervals for future...

Models of glucose metabolism can help to simulate and predict the blood glucose response in hyperglycaemic, critically ill patients. Model prediction performance depends on a sufficiently accurate estimation of the patient’s time-varying insulin sensitivity. The work presents three least squares approaches, the integral method and a Bayesian method that have been compared by prediction accuracy...

Horizontal directional drilling is usually used in drilling engineering. In a variety of conditions, it is necessary to predict the torque required for performing the drilling operation. Nevertheless, there is presently not a convenient method available to accomplish this task. In order to overcome this difficulty, the current work aims at predicting the required rotational torque (RT) to opera...

The reliability of a multidimensional test instrument is commonly estimated using coefficients ωt (total) and ωh (hierarchical). However, point estimates for the are rarely accompanied by uncertainty estimates. In this study, we compare bootstrap normal-theory confidence intervals. addition, develop Bayesian versions sampling from second-order factor model. Results comprehensive simulation stud...