Lateral spreading is one of the most destructive effects of liquefaction. Liquefaction is known as one of the major causes of ground failure related to earthquake. This phenomenon is likely to occur when the rate of earthquake-induced excess pore water pressure buildup exceeds the rate of drainage. Estimation of the hazard of lateral spreading requires characterization of subsurface conditions....

This paper shows that standard empirical methods for estimating log-linearized consumption Euler equations cannot successfully uncover structural parameters like the coefficient of relative risk aversion from a dataset of simulated consumers behaving exactly according to the standard model. Furthermore, consumption growth for the simulated consumers is very highly statistically related to predi...

A computer model of a single screw oil-flooded low pressure air compressor was developed which predicts the internal conditions based on certain empirical values. A characteristic thread technique is used for steady state operation. A polytropic process is used and the model will iterate for the polytropic coefficient to best correlate internal predictions with empirical values. The geometric v...

The consistency of the quasi maximum likelihood estimator for random coefficient autoregressive models requires that the coefficient be a non-degenerate random variable. In this paper we propose empirical likelihood methods based on weighted score equations to construct a confidence interval for the coefficient. We do not need to distinguish whether the coefficient is random or deterministic an...

In this article we propose a method of performing arithmetic operations on variables with unknown distribution. The approach to the evaluation results of arithmetic operations can select probability intervals of the algebraic equations and their systems solutions, of differential equations and their systems in case of histogram evaluation of the empirical density distributions of random paramet...

An innnite system of stochastic diierential equations for the locations and weights of a collection of particles is considered. The particles interact through their weighted empirical measure, V , and V is shown to be the unique solution of a nonlinear stochastic partial diierential equation (SPDE). Conditions are given under which the weighted empirical measure has an L 2-density with respect ...

Data warehouses (DWs) can become inconsistent when some dimensional constraints are not satisfied by the dimension instances. In this paper, we present preliminary results about the effects of the violation of partitioning constraints in homogeneous dimension instances over aggregation queries, and in particular over the summarizability property (SUMM) of the DWs. We are interested in finding w...

The purpose of this paper is to discuss empirical risk minimization when the losses are not necessarily bounded and may have a distribution with heavy tails. In such situations usual empirical averages may fail to provide reliable estimates and empirical risk minimization may provide large excess risk. However, some robust mean estimators proposed in the literature may be used to replace empiri...

In this note we study lower bounds on the empirical minimization algorithm. To explain the basic set up of this algorithm, let (Ω, μ) be a probability space and set X to be a random variable taking values in Ω, distributed according to μ. We are interested in the function learning (noiseless) problem, in which one observes n independent random variables X1, . . . , Xn distributed according to μ...

We develop an empirical likelihood (EL) inference on parameters in generalized estimating equations with nonignorably missing response data. We consider an exponential tilting model for the nonignorably missing mechanism, and propose modified estimating equations by imputing missing data through a kernel regression method. We establish some asymptotic properties of the EL estimators of the unkn...