This paper describes a simple method of calculating a heteroskedasticity and autocorrelation consistent covariance matrix that is positive semi-definite by construction. It also establishes consistency of the estimated covariance matrix under fairly general conditions. (This abstract was...

This paper is primarily concerned with extending the results of Stein to spherically symmetric distributions. Specifically, when X ∼f(||X - θ||2), we investigate conditions under which estimators of the form X ag(X) dominate X for loss functions ||δ- θ||2 and loss functions which are...

The problem considered is the estimation of "k" coefficients of interest in a linear regression model when the (k+1)st coefficient is of no interest. It is shown that this problem is equivalent to the problem of estimating the unknown mean of a univariate normal distribution with variance one...

Network-Centric Meaning-Driven Human-Centric AI-Cyber Computing Beyond Data-Driven to Event-Driven Architectures for Quantum Uncertainty, 1995-2023:Building upon the contextual focus of current global worldwide discussions on GPT, ChatGPT, GenAI, Generative AI, Large Language Model - LLMs, we...

Goal: ISO 31000 Risk Management (RM) recently re-defined risk as the effect of uncertainty on an organization's ability to meet the objectives. Earlier, it defined risk as a combination of the probability and scope of the (predicted) consequences. The revised ISO Risk advances beyond a static...

In the aftermath of the Global Financial Crisis, some risk management practitioners have advocated wider adoption of Bayesian inference to replace Value- at-Risk (VaR) models in order to minimize risk failures. Despite its limitations, the Bayesian methodology has significant advantages. Just...

Non-life insurance companies most especially, are often faced with the challenge of predicting the number of claims and claim amount to be incurred at any given time. Overcoming such challenges requires examining claim patterns, which assists in premium determination and setting of reserves. The...

In aftermath of the Financial Crisis, some risk management practitioners advocate wider adoption of Bayesian inference to replace Value-at-Risk (VaR) models for minimizing risk failures (Borison & Hamm, 2010). They claim reliance of Bayesian inference on subjective judgment, the key limitation...

Many unit root and cointegration tests require an estimate of the spectral density function at frequency zero at some process. Kernel estimators based on weighted sums of autocovariances constructed using estimated residuals from an AR(1) regression are commonly used. However, it is known that...

In this paper we analyse the problem of the modelling of individual transitions in presence of an incomplete sampling scheme. This problem is particularly cumbersome when a continuous-time scale is used for the modelling and when the model incorporates unobserved heterogeneity. This problem...