Risk factor selection is very important in the insurance industry, which helps precise rate
making and studying the features of high‐quality insureds. Zero‐inflated data are common in …

In this paper, we consider structure detection and parameter estimation of the nonlinear auto-
regressive with exogenous inputs (NARX) model, using the EM (expectation–maximisation) …

Solving a constructed-response item usually requires successfully performing a sequence of
tasks. Each task could involve different attributes, and those required attributes may be …

Abstract Sequential Monte Carlo (SMC) is a powerful technique originally developed for
particle filtering and Bayesian inference. As a generic optimizer for statistical and …

We present a frequentist-based approach to forecast time series in the presence of in-
sample and out-of-sample breaks in the parameters of the forecasting model. We first model …

A common belief is to qualify the credit default swap (CDS) market as very liquid. However,
looking at intra-daily CDS data on individual firms from a major interdealer broker, we find …

We propose an algorithm for optimal input design in nonlinear stochastic dynamic systems.
The approach relies on minimizing a function of the covariance of the parameter estimates of …

This paper analyzes the interdealer-broker market for single-name Credit Default Swaps
(CDSs) using a novel dataset from the GFI trading platform. We find that CDSs exhibit …

This paper analyzes stock-price volatility in the presence of periodically collapsing Evans
bubbles. We derive a volatility formula that establishes a link between the bubble …

Everyday life actuators such as music can be used as neurofeedback to improve quality of
life and performance. To track one's performance, we develop a performance decoder that …