A common assumption in supervised learning is that the training and test input points follow the same probability distribution. However, this assumption is not fulfilled, e.g., in interpolation, extrapolation, or active learning scenarios. The violation of this assumption— known as the covariate shift—causes a heavy bias in standard generalization error estimation schemes such as cross-validati...

Empirical tests of the arbitrage pricing theory using measured variables rely on the accuracy of standard inferential theory in approximating the distribution of the estimated risk premiums and factor betas. The techniques employed thus far perform factor selection and model inference sequentially. Recent advances in Bayesian variable selection are adapted to an approximate factor model to inve...

background: several epidemiological studies conducted on underground miner’s show that exposure to elevated levels of radioactive radon gas is expected to increase the risk of lung cancer. relative risk of lung cancer is almost linear with radon exposure. elevated concentrations of radon are not only reported within mines but also for closed indoor environment of general public houses. measurem...

Value-at-risk (VaR) and conditional value-at-risk (CVaR) are popular risk measures from academic, industrial and regulatory perspectives. The problem of minimizing CVaR is theoretically known to be of a Neyman–Pearson type binary solution. We add a constraint on expected return to investigate the mean-CVaR portfolio selection problem in a dynamic setting: the investor is faced with a Markowitz ...

Some insurance markets are characterized by “advantageous selection”, that is, ex-post risk and coverage are negatively correlated. We show that expectation-based loss aversion as in Kőszegi and Rabin (2006, 2007) provides a natural explanation for this phenomenon when agents face modest-scale risks. More exposure to risk has two competing effects on an agent’s willingness to pay for insurance:...

This paper utilizes a probabilistic mold risk assessment method, introducing a novel mold risk indicator (MRI). The MRI captures the risk of mold occurrence at identified “trouble spots” under uncertainty. It will show how the MRI can enhance decision-making in a mold remediation case. When used in decision making under uncertainty, the MRI enables the best selection of remediation actions in t...

Selection of genotypes based on high value of heritability and forecasted genetic conditions would be an effective method for improvement of wheat cultivars. The present investigation was carried out to estimate the genetic variability of agro-physiological characters using biometrical genetic techniques in 20 bread wheat genotypes under irrigated condition. For this purpose an experiment was c...