In model-based software development, models are core development artifacts which are typically created and modified by multiple developers over a period of time. In order to be able to reason about the evolution of models, the computation of the differences between different versions of a model, called model differencing, is a crucial activity. However, in general a completely automatic approac...

We present a new method, median filtered differencing, for estimation of tangentdirection and curvature of digitised curves. On three synthetic examples and two images we show the algorithm performs successfully on both straight and curved segments even in the neighbourhood of discontinuities.

In a recent paper Jun Arima formalises the idea of preduc-tion { a non-monotonic schema providing a common basis for inductive and analogical reasoning. We examine some of the implications of this schema, as well as its connections with prototypes and conceptual spaces. A generalised version of his schema is motivated and developed to address diiculties with asymmetry and disjuncts.

We discuss computational aspects of likelihood-based estimation of univariate ARFIMA(p, d, q) models. We show how efficient computation and simulation is feasible, even for large samples. We also discuss the implementation of analytical bias corrections.

1Department of Communicable Disease Control and Prevention, Jämtland County Council, Östersund, Sweden; 2Department of Clinical Microbiology, Unit of Clinical Research CenterÖstersund, Umeå University, Umeå, Sweden; 3Centre of Registers in Northern Sweden, Umeå University, Umeå, Sweden; 4Swedish Health Care Direct 1177, Jämtland County Council, Östersund, Sweden; 5Department of Clinical Microbi...

Since the publication of the Bellcore measurements in the early nineties, long-range dependence (LRD) has been in the center of a continuous debate within the teletraac community. While researchers largely acknowledge the signiicance of the LRD phenomenon, they still disagree on two issues: (1) the utility of LRD models in buuer dimensioning and bandwidth allocation, and (2) the ability of comm...

Morehead City, North Carolina, faced a moratorium on new construction because of problems with its sewage system. We developed an autoregressive integrated moving average (ARIMA) transfer function-intervention model to help town officials explain the sources of variation in the volume of sewage-treatment-plant discharge to the state officials who had imposed the moratorium on extending the sewa...

In many intervention analysis applications, time series data may be expensive or otherwise difficult to collect. In this case the power function is helpful, because it can be used to determine the probability that a proposed intervention analysis application will detect a meaningful change. Assuming that an underlying autoregressive integrated moving average (ARIMA) or fractional ARIMA model is...

Durbin’s methods for moving average (MA) and autoregressive-moving average (ARMA) estimation use the parameters of a long AR model to compute the MA parameters. Linear regression theory is applied to find the best AR order. This yields two different orders: one for the best predicting AR model and another one for the long AR model with the best parameter accuracy, as intermediate for Durbin’s e...

This paper discusses three modelling techniques, which apply to multiple time series data that correspond to different spatial locations (spatial time series). The first two methods, namely the Space-Time ARIMA (STARIMA) and the Bayesian Vector Autoregressive (BVAR) model with spatial priors apply when interest lies on the spatio-temporal evolution of a single variable. The former is better sui...