Computational Statistics is an international journal that fosters the publication of applications and methodological research in the field of computational statistics. In this article, we will discuss the motivation, history, some specialties, and the future scope of this journal

We propose a modified version of the augmented Kalman filter (AKF) to evaluate the likelihood of linear and time-invariant state-space models (SSMs). Unlike the regular AKF, this augmented steady-state Kalman filter (ASKF), as we call it, is based on a steady-state Kalman filter (SKF). We show...

In this study, we derive the joint asymptotic distributions of functionals of quantile estimators (the non-parametric sample quantile and the parametric location-scale quantile) and functionals of measure of dispersion estimators (the sample standard deviation, sample mean absolute deviation,...

Pearson's chi-square test is widely employed in social and health sciences to analyze categorical data and contingency tables. For the test to be valid, the sample size must be large enough to provide a minimum number of expected elements per category. This paper develops functions for...

Uncertainty in regression can be efficiently and effectively communicated using the visual properties of statistical objects in a regression display. Altering the "visual weight" of lines and shapes to depict the quality of information represented clearly communicates statistical confidence,...

In the microsimulation literature, it is still uncommon to test the statistical significance of results. In this paper we argue that this situation is both undesirable and unnecessary. Provided the parameters used in the microsimulation are exogenous, as is often the case in static...

In this paper, we develop a new model-based method to inference on totals and averages of nite populations segmented in planned domains or strata. Within each stratum, we decompose the total as the sum of its sampled and unsampled parts, making inference on the unsampled part using Bayesian...

This paper extends two optimization routines to deal with objective functions for DSGE models. The optimization routines are i) a version of Simulated Annealing developed by Corana, Marchesi amp; Ridella (1987), and ii) the evolutionary algorithm CMA-ES developed by Hansen, Muuml;ller amp;...