Semiautomatic robust regression clustering of international trade data
The purpose of this paper is to show in regression clustering how to choose the most
relevant solutions, analyze their stability, and provide information about best combinations of …
relevant solutions, analyze their stability, and provide information about best combinations of …
Newcomb–Benford law and the detection of frauds in international trade
The contrast of fraud in international trade is a crucial task of modern economic regulations.
We develop statistical tools for the detection of frauds in customs declarations that rely on …
We develop statistical tools for the detection of frauds in customs declarations that rely on …
robROSE: A robust approach for dealing with imbalanced data in fraud detection
B Baesens, S Höppner, I Ortner, T Verdonck - Statistical Methods & …, 2021 - Springer
A major challenge when trying to detect fraud is that the fraudulent activities form a minority
class which make up a very small proportion of the data set. In most data sets, fraud occurs …
class which make up a very small proportion of the data set. In most data sets, fraud occurs …
Goodness-of-fit testing for the Newcomb-Benford law with application to the detection of customs fraud
The Newcomb-Benford law for digit sequences has recently attracted interest in antifraud
analysis. However, most of its applications rely either on diagnostic checks of the data, or on …
analysis. However, most of its applications rely either on diagnostic checks of the data, or on …
Evolving principal component clustering with a low run-time complexity for LRF data mapping
In this paper a new approach called evolving principal component clustering is applied to a
data stream. Regions of the data described by linear models are identified. The method …
data stream. Regions of the data described by linear models are identified. The method …
[HTML][HTML] Simulating mixtures of multivariate data with fixed cluster overlap in FSDA library
We extend the capabilities of MixSim, a framework which is useful for evaluating the
performance of clustering algorithms, on the basis of measures of agreement between data …
performance of clustering algorithms, on the basis of measures of agreement between data …
On characterizations and tests of Benford's law
Benford's law defines a probability distribution for patterns of significant digits in real
numbers. When the law is expected to hold for genuine observations, deviation from it can …
numbers. When the law is expected to hold for genuine observations, deviation from it can …
Forum on Benford's law and statistical methods for the detection of frauds
L Barabesi, A Cerioli, D Perrotta - Statistical Methods & Applications, 2021 - Springer
This forum intends stimulating cross-domain research in Benford's law theory and robust
statistics. Our point of view is introduced in Sect. 2, with the intention to show the rationale …
statistics. Our point of view is introduced in Sect. 2, with the intention to show the rationale …
Assessing trimming methodologies for clustering linear regression data
We assess the performance of state-of-the-art robust clustering tools for regression
structures under a variety of different data configurations. We focus on two methodologies …
structures under a variety of different data configurations. We focus on two methodologies …
Modeling international trade data with the Tweedie distribution for anti-fraud and policy support
This paper shows the potential of the Tweedie distribution in the analysis of international
trade data. The availability of a flexible model for describing traded quantities is important for …
trade data. The availability of a flexible model for describing traded quantities is important for …