Markov chain Monte Carlo (MCMC) methods have an important role in solving high dimensionality stochastic problems characterized by computational complexity. Given their critical importance, there is need for network and security risk management research to relate the MCMC quantitative...

This paper analyzes the higher-order properties of nested pseudo-likelihood (NPL) estimators and their practical implementation for parametric discrete Markov decision models in which the probability distribution is defined as a fixed point. We propose a new NPL estimator that can achieve...

Virtually each seasonal adjustment software includes an ensemble of seasonality tests for assessing whether a given time series is in fact a candidate for seasonal adjustment. However, such tests are certain to produce either the same resultor conflicting results, raising the question if there...

Six permutation test algorithms coded in SAS® are compared. The fastest (“OPDN”), which uses no modules beyond Base SAS®, achieves speed increases orders of magnitude faster than the relevant “built-in” SAS® procedures (over 215x faster than Proc SurveySelect, over 350x faster than...

While permutation tests and bootstraps have very wide-ranging application, both share a common potential drawback: as data-intensive resampling methods, both can be runtime prohibitive when applied to large or even medium-sized data samples drawn from large datasets. The data explosion over the...

In this paper, we propose a novel entropy-based resampling scheme valid for non-stationary data. In particular, we identify the reason for the failure of the original entropy-based algorithm of Vinod and Lopez-de Lacalle (2009) to be the perfect rank correlation between the actual and...

Tail risk refers to the possibility that a rare event would adversely affect the value of a portfolio in a significant manner. It became much more relevant due to recent periods of strong market turbulence.We describe how to quantify such risk, which tail risk protection strategies were...

Virtually each seasonal adjustment software includes an ensemble of seasonality tests for assessing whether a given time series is in fact a candidate for seasonal adjustment. However, such tests are certain to produce either the same resultor conflicting results, raising the question if there...

Virtually each seasonal adjustment software includes an ensemble of seasonality tests for assessing whether a given time series is in fact a candidate for seasonal adjustment. However, such tests are certain to produce either the same resultor conflicting results, raising the question if there...