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Ridge-based method for finding curvilinear structures from noisy data

Pulkkinen, Seppo - In: Computational Statistics & Data Analysis 82 (2015) C, pp. 89-109

as sampling noise and background clutter. It is shown that ridge curves of the marginal density induced by the model can … be used to estimate the generating functions. Given a Gaussian kernel density estimate for the marginal density, ridge …–corrector algorithm for tracing the ridge curve set of such a density estimate is developed. Efficiency and robustness of the algorithm …

Persistent link: https://www.econbiz.de/10011117702

Monetary Valuation of Aircraft Noise

Dekkers, Jasper; van der Straaten, Willemijn - 2008

In densely-populated countries and in particular in large metropolitan areas, the presence of so much human activity causes all sorts of negative externalities, for example traffic noise disturbance. These externalities call for corrective measures by the government. Economists have developed a...

Persistent link: https://www.econbiz.de/10010325998

Context-Based Scene Understanding

Furht, Borko; Zolghadr, Esfandiar - In: International Journal of Multimedia Data Engineering … 7 (2016) 1, pp. 22-40

Context plays an important role in performance of object detection. There are two popular considerations in building context models for computer vision applications; type of context (semantic, spatial, scale) and scope of the relations (pairwise, high-order). In this paper, a new unified...

Persistent link: https://www.econbiz.de/10012046501

On D-Optimality Based Trust Regions for Black-Box Optimization Problems

Brekelmans, Ruud; Den Hertog, Dick; Driessen, L.; … - Tilburg University, Center for Economic Research - 2001

In this paper we show how techniques from response surface methodology and mathematical programming can be combined into a new sequential derivative-free approach for solving unconstrained deterministic black-box optimization problems.In this sequential derivative-free optimization approach...

Persistent link: https://www.econbiz.de/10011091046

Gradient trust region algorithm with limited memory BFGS update for nonsmooth convex minimization

Yuan, Gonglin; Wei, Zengxin; Wang, Zhongxing - In: Computational Optimization and Applications 54 (2013) 1, pp. 45-64

By means of a gradient strategy, the Moreau-Yosida regularization, limited memory BFGS update, and proximal method, we propose a trust-region method for nonsmooth convex minimization. The search direction is the combination of the gradient direction and the trust-region direction. The global...

Persistent link: https://www.econbiz.de/10010896513

Non-linear noise reduction and detecting chaos: some evidence from the S&P Composite Price Index

Harrison, Robert G.; Yu, Dejin; Oxley, Les; Lu, Weiping; … - In: Mathematics and Computers in Simulation (MATCOM) 48 (1999) 4, pp. 497-502

Academic and applied researchers in economics have, in the last 10 years, become increasingly interested in the topic of chaotic dynamics. In this paper we undertake non-linear dynamical analysis of one representative time series taken from financial markets, namely the Standard and Poor's (S&P)...

Persistent link: https://www.econbiz.de/10011050980

Price clustering and discreteness: is there chaos behind the noise?

Antoniou, Antonios; Vorlow, Constantinos E. - In: Physica A: Statistical Mechanics and its Applications 348 (2005) C, pp. 389-403

We investigate the “compass rose” patterns introduced by Crack and Ledoit (J. Finance 51(2)(1996) 751) as revealed in phase portraits (delay plots) of stock returns. The structures observed in these diagrams have been attributed mainly to price clustering and discreteness and the tick size....

Persistent link: https://www.econbiz.de/10011063370

Effective PCA for high-dimension, low-sample-size data with noise reduction via geometric representations

Yata, Kazuyoshi; Aoshima, Makoto - In: Journal of Multivariate Analysis 105 (2012) 1, pp. 193-215

In this article, we propose a new estimation methodology to deal with PCA for high-dimension, low-sample-size (HDLSS) data. We first show that HDLSS datasets have different geometric representations depending on whether a ρ-mixing-type dependency appears in variables or not. When the...

Persistent link: https://www.econbiz.de/10011041986

Overlapping community detection using a generative model for networks

Wang, Zhenwen; Hu, Yanli; Xiao, Weidong; Ge, Bin - In: Physica A: Statistical Mechanics and its Applications 392 (2013) 20, pp. 5218-5230

Detecting overlapping communities is a challenging task in analyzing networks, where nodes may belong to more than one community. Many present methods optimize quality functions to extract the communities from a network. In this paper, we present a probabilistic method for detecting overlapping...

Persistent link: https://www.econbiz.de/10010742306

A continuation approach to mode-finding of multivariate Gaussian mixtures and kernel density estimates

Pulkkinen, Seppo; Mäkelä, Marko; Karmitsa, Napsu - In: Journal of Global Optimization 56 (2013) 2, pp. 459-487

Gaussian mixtures (i.e. linear combinations of multivariate Gaussian probability densities) appear in numerous applications due to their universal ability to approximate multimodal probability distributions. Finding the modes (maxima) of a Gaussian mixture is a fundamental problem arising in...

Persistent link: https://www.econbiz.de/10010994087