-cause failure models have limitations in a simulation environment. In addition, substantial subjectivity is associated with … estimate parameters in traditional common-cause failure models. Simulation examples are presented for failures in time. The … perform the Bayesian inference via Markov chain Monte Carlo sampling. …

module. VSP 2.0, on the other hand, has over 20 sampling goals, allowing the user to input site-specific assumptions such as …-sample comparisons, perform confidence interval estimation, use sequential search sampling methods, and much more. Over 1,000 copies of …

modeling in ToolKit until the TPP standard is met. Increased wholesale market price volatility and six years of drought have … receiving those funds is greater. In addition to market price volatility, BPA also faces uncertainty around the financial …

factor model with that of the heavy tailed univariate stochastic volatility model. A unified analysis of the model, and its … algorithm (which relies on MCMC methods) are: (1) a reduced blocking scheme for sampling the free elements of the loading matrix … and the factors and (2) a special method for sampling the parameters of the univariate SV process. The resulting algorithm …

volatility on foreign exchange markets. Starting point is the market participant's microeconomic investment decision, which is … trading volume and volatility on foreign exchange markets. We apply various two-country-models with representative market …

into volatility persistence in stock returns. In part two, I show that the introduction of continuous trading on the WSE is … volatility on days after limit hits and positive autocorrelation in stock returns. I do not find significant advantages of this …

user determine the optimal number and location of samples using defensible statistical sampling design methods and displays … summarizing the assumptions and parameter inputs is generated and can be included in a sampling and analysis plan. VSP features …

In order to devise an algorithm for autonomously terminating Monte Carlo sampling when sufficiently small and reliable … rejected as not being true 95% CI at less than a 40% chance of incorrect rejection. With regard to Latin Hypercube sampling …

, simulation techniques, and statistical reasoning, the discussion here appears to provide reasonable estimates of the truth. The …