Hierarchical models are considered for estimating the probability of agreement between two outcomes or endpoints from an environmental
toxicity experiment. Emphasis is placed on generalized regression models, under which the prior mean is related to a linear
combination of explanatory variables via a monotone function. This function defines the scale over which the systematic effects
are modelled as additive. Specific illustration is provided for the logistic link function. The hierarchical model employs
a conjugate beta prior that leads to parametric empirical Bayes estimators of the individual agreement parameters. An example
from environmental carcinogenesis illustrates the methods, with motivation derived from estimation of the concordance between
two species carcinogenicity outcomes. Based on a large database of carcinogenicity studies, the inter-species concordance
is seen to be reasonably informative, i.e. in the range 67–84%. Stratification into pertinent potency-related sub-groups via
the logistic model is seen to improve concordance estimation: for environmental stimuli at the extremes of the potency spectrum,
concordance can reach well above 90%. 相似文献
Objectives: The uncertainties of pedestrian mobility are important factors affecting the accuracy and robustness of an active pedestrian protection system. This study is to provide the means for probabilistic risk evaluation of pedestrian–vehicle collision by counting the uncertainties in pedestrian motion.
Method: The pedestrian is modeled by a first-order Markov model to characterize the stochastic properties in mobility according to field experiments of pedestrians crossing an uncontrolled road. Based on the assumption of Gaussian distribution, unscented transformation (UT) is employed to predict the collision risk probability with the symmetric σ-set constructed on the basis of discrete trajectory simulation. Simulation experiments were carried out with 10,000 Monte Carlo (MC) simulations as the reference.
Results: The probability density distributions of time-to-collision, minimal distance, and collision probability estimated by UT coincide with the reference ones under various vehicle–pedestrian conflict scenarios, and the maximal deviation of collision probability from the reference is 5.33%. The UT method is about 600 times faster than the MC method (10,000 runs), which means that the proposed method has the potential for online application.
Conclusions: This article presents an effective and efficient algorithm to estimate the collision probability by using a UT method to solve the nonlinear transformation of uncertainties in pedestrian motion. Simulation results show that the UT-based method achieves accurate collision probability estimation and higher computation efficiency than MC and provides more valuable information concerning collision avoidance than the deterministic methods in the design of a pedestrian collision avoidance system. 相似文献