ESTIMATING UNCERTAINTY IN MULTIVARIATE RESPONSES TO SELECTION

Estimating uncertainty in multivariate responses to selection.

Predicting the responses to natural selection is one of the key goals of evolutionary biology. Two of the challenges in fulfilling this goal have been the realization that many estimates of natural selection might be highly biased by environmentally induced covariances between traits and fitness, and that many estimated responses to selection do not incorporate or report uncertainty in the esti...

Estimating Aversion to Uncertainty

It is intuitive that decision-makers might have attitudes towards uncertainty just as they might have attitudes towards risk. However, it is only recently that this intuitive notion has been formalized and axiomatically characterized. We estimate the extent of uncertainty aversion in a manner that is parsimonious and consistent with theory. We demonstrate that one can jointly estimate attitudes...

Understanding a Version of Multivariate Symmetric Uncertainty to assist in Feature Selection

In this paper, we analyze the behavior of the multivariate symmetric uncertainty (MSU) measure through the use of statistical simulation techniques under various mixes of informative and non-informative randomly generated features. Experiments show how the number of attributes, their cardinalities, and the sample size affect the MSU. We discovered a condition that preserves good quality in the ...

Estimating stability and selection index

Estimating Measurement Uncertainty

Most analytical methods are relative and hence require calibration. Calibration measurements are normally performed with reference materials or calibration standards. Typically least squares methods have been employed in such a manner as to ignore uncertainties associated with the calibration standards. However different authors [3, 4, 11] have shown that by taking into account the uncertaintie...