Analysis and design of structural systems always requires the treatment of uncertainties by using statistical and probabilistic concepts so this can be done in a rational way. It is shown that traditional, deterministic concepts can be easily extended to account for uncertainties. The so-called Monte Carlo Simulation procedures are the key for these developments. By this method, deterministic m...

A review of the literature suggests that few studies use formative indicator measurement models, even though they should. Therefore, the purpose of this research is to (a) discuss the distinction between formative and reflective measurement models, (b) develop a set of conceptual criteria that can be used to determine whether a construct should be modeled as having formative or reflective indic...

The problem of hypothesis testing and interval estimation of the reliability parameter in a stress–strength model involving two-parameter exponential distributions is considered. Test and interval estimation procedures based on the generalized variable approach are given. Statistical properties of the generalized variable approach and an asymptotic method are evaluated by Monte Carlo simulation...

This paper proposes a procedure for testing and classifying stability data with multiple factors. A two-way analysis of covariance is used to classify the diierences among the batches as well as another factor such as package type and/or product strength. In the test procedure, slopes and intercepts of the main eeects are tested using a combination of simultaneous and sequential F-tests. Based ...

The idea of real option is applied in military software pricing in this paper. By analysis of Black-Scholes pricing model, we figure two crucial variables. One is value of software option that is regarded as estimated cost in our study. We give the logical analysis based on the option feature of estimated cost and also the practical test by building up a system of equations. The other one is th...

This research proposes that, in cases where threshold covariates are either unavailable or difficult to observe, practitioners should treat these characteristics as latent, and use simulated maximum likelihood techniques to control for them. Two econometric frameworks for doing so in a more flexible manner are proposed. The finite sample performance of these new specifications are investigated ...

We discuss in this work the validity of the theoretical solution of the nonlinear Couette flow for a granular impurity obtained in a recent work [preprint arXiv:0802.0526], in the range of large inelasticity and shear rate. We show there is a good agreement between the theoretical solution and Monte Carlo simulation data, even under these extreme conditions. We also discuss an extended theoreti...

Let μ be a p-dimensional vector, and let Σ1 and Σ2 be p × p positive definite covariance matrices. On being given random samples of sizes N1 and N2 from independent multivariate normal populations Np(μ,Σ1) and Np(μ,Σ2), respectively, the Behrens-Fisher problem is to solve the likelihood equations for estimating the unknown parameters μ, Σ1, and Σ2. We shall prove that for N1, N2 > p there are, ...

Concurrent learning is a recently developed adaptive update scheme that can be used to guarantee parameter convergence without requiring persistent excitation. However, this technique requires knowledge of state derivatives, which are usually not directly sensed and therefore must be estimated. A novel integral concurrent learning method is developed in this paper that removes the need to estim...