Geoscience after IT: Part F. Familiarization with quantitative analysis

Numbers, measurement and calculation extend our view of the world. Statistical methods describe the properties of sets of quantitative data, and can test models (particularly the model that observed relationships arose by chance) and help us to draw conclusions. Links between spatial and quantitative methods, through coordinate geometry and matrix algebra, lead to graphical representations for visualizing and exploring relationships. Multivariate statistics tie into visualization to look at pattern among many properties

Calibration and improved prediction of computer models by universal Kriging

This paper addresses the use of experimental data for calibrating a computer model and improving its predictions of the underlying physical system. A global statistical approach is proposed in which the bias between the computer model and the physical system is modeled as a realization of a Gaussian process. The application of classical statistical inference to this statistical model yields a rigorous method for calibrating the computer model and for adding to its predictions a statistical correction based on experimental data. This statistical correction can substantially improve the calibrated computer model for predicting the physical system on new experimental conditions. Furthermore, a quantification of the uncertainty of this prediction is provided. Physical expertise on the calibration parameters can also be taken into account in a Bayesian framework. Finally, the method is applied to the thermal-hydraulic code FLICA 4, in a single phase friction model framework. It allows to improve the predictions of the thermal-hydraulic code FLICA 4 significantly

Mortality risk and the valuation of annuities with guaranteed minimum death benefit options: application to the Italian population

In this note, we describe the payoff of Guaranteed Minimum Death Benefit options (GMDB) embedded in annuity contracts and discuss their valuation using data for the Italian male population as a case study. These put options have stochastic maturity dates due to the involuntary exercise at the moment of death. We value the GMDB as a weighted average price of a set of deterministic put options with different maturity dates, where the weights are the probability of death at every date. We take into account the mortality risk and investigate the sensitivity of the price of the option to changes in mortality probability using both deterministic and stochastic approaches

tolerance: An R Package for Estimating Tolerance Intervals

The tolerance package for R provides a set of functions for estimating and plotting tolerance limits. This package provides a wide-range of functions for estimating discrete and continuous tolerance intervals as well as for estimating regression tolerance intervals. An additional tool of the tolerance package is the plotting capability for the univariate and regression settings as well as for the multivariate normal setting. The tolerance package's capabilities are illustrated using simulated data sets. Formulas used for the estimation procedures are also presented.

Studies on chain sampling schemes in quality and reliability engineering

Ph.DDOCTOR OF PHILOSOPH