doi:10.3850/978-981-08-5118-7_021

ABSTRACT

In the geotechnical determination of the cohesion c and the angle of internal friction φ of a soil from shear tests, a linear regression model is fitted to normal and shear stress data, and confidence bounds are computed. The applicability of standard linear regression is limited by the physical requirement of nonnegative cohesion and the statistical requirement of normality. We propose two methods from computational statistics that are able to overcome both obstacles: a bootstrap resampling method in case the experimental data set is sufficiently large, and a Bayesian approach for small samples. The methods are demonstrated at the hand of a real data set for glacial till.

Keywords: Shear parameters, Non-normal regression, Bayesian methods, Bootstrap confidence intervals, Computational statistics.

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