Building better confidence intervals for the resistance factor in LRFD
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Engineers employ the LRFD model system in the planning and development of structures (e.g. bridges, highways, buildings). The system takes into account the load the structure will bear and the resistance of the structure against that load. Of interest in the LRFD system is the resistance factor (φ) that affects the resistance. Samples are collected to estimate φ, but the estimate (φ ̂ ) has typically been treated as a deterministic number; when instead, it should be viewed as a random variable. This thesis examines the performance of one method of proposed confidence intervals for φ ̂ , investigates the sampling distribution of φ ̂, and proposes improvements upon the existing method. A bootstrap simulation process is employed to evaluate the performance of the proposed method (nonparametric and parametric) through the metrics of coverage and relative interval length. Additionally, another simulation is used to determine the distribution of the estimator (φ ̂). Finally, remedial measures for the original interval method are proposed, implemented, and investigated via simulations.