A multifidelity approach to design and analysis for complex systems seeks to exploit optimally all available models and data. Existing multifidelity approaches generally attempt to calibrate low-fidelity models or replace low-fidelity analysis results using data from higher fidelity analyses. This paper proposes a fundamentally different approach that uses the tools of estimation theory to fuse...

In single-period portfolio optimization several facets of the problem may influence the goodness of the portfolios selected. Despite that, some of these facets are frequently ignored when the optimization problem is solved. In this thesis, we aim at investigating the impact of these facets on the optimization problem and on the performances of the portfolios selected. Firstly, we consider the p...

The performance of a multidisciplinary system is inevitably affected by various sources of uncertainties, usually categorized as aleatory (e.g. input variability) or epistemic (e.g. model uncertainty) uncertainty. In the framework of design under uncertainty, all sources of uncertainties should be aggregated to assess the uncertainty of system quantities of interest (QOIs). In a multidisciplina...

For expensive black-box optimization problems, surrogatemodel based approaches like Efficient Global Optimization are frequently used in continuous optimization. Their main advantage is the reduction of function evaluations by exploiting cheaper, data-driven models of the actual target function. The utilization of such methods in combinatorial or mixed search spaces is less common. Efficient Gl...

Design optimization can lead to structures, which are susceptible to even small uncertainties especially in terms of stability. Stability against buckling is a response, which is critical to structural integrity. The consideration of uncertainty is vital to understanding the behavior of the real structure as uncertainties are unavoidable. In this study fuzzy models for imprecise material and lo...

When analysing the efficiency of decision-making units, robustness scores to changes in data is desirable, especially context managerial or regulatory benchmarking. However, maximum likelihood estimation stochastic frontier models remains underexplored. We examine behaviour influence function estimator a context, and derive some sufficient conditions for robust terms properties marginal distrib...

Motivated by the availability of continuous event sequences that trace the social behavior in a population e.g. email, we believe that mutually exciting Hawkes processes provide a realistic and informative model for these sequences. For complex mutually exciting processes, the numerical optimization used for univariate self exciting processes may not provide stable estimates. Furthermore, conve...

In this paper, we propose a novel joint semi-blind channel and data estimation technique based on Whitening Rotation (WR) method for Rayleigh flat fading Multiple Input Multiple output (MIMO) channel using different receiver antennas combinations. Here we divide newly proposed technique in three steps. In the first step, we use conventional Whitening Rotation based semi-blind channel estimation...

In many cases, finding a maximum likelihood estimator or a Generalized Likelihood Ratio Test estimate becomes an optimization problem. The challenges come when the problem is not formulated as what we usually see, or the size of the problem is too large to be manageable by conventional methods. We present three examples that have this flavor. They are (1) finding the maximum likelihood estimate...