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HU, TIANMIN; SUNG, SAM YUAN - In: International Journal of Information Technology & … 04 (2005) 02, pp. 251-262

Outlier detection targets those exceptional data whose pattern is rare and lie in low density regions. In this paper, under the assumption of complete spatial randomness inside clusters, we propose an MDV (Multi-scale Deviation of the Volume) approach to identifying outliers. In addition to...

Persistent link: https://www.econbiz.de/10005033356

Effectiveness of Heuristic Based Approach on the Performance of Indexing and Clustering of High Dimensional Data

Chen, Alan; Gao, Shang; Jarada, Tamer N.; Zhang, Ming; … - In: Journal of Information & Knowledge Management (JIKM) 10 (2011) 03, pp. 261-271

utilised a number of clustering techniques, including the agglomerative hierarchical clustering, k-means clustering, and DBSCAN … attention in the research community. Indexing and clustering of high dimensional data are two of the most challenging techniques … technique applicable to indexing and clustering algorithms which need to calculate distances and check them against some minimum …

Persistent link: https://www.econbiz.de/10009274282

Ultrahigh dimensional variable selection through the penalized maximum trimmed likelihood estimator

Neykov, N.; Filzmoser, P.; Neytchev, P. - In: Statistical Papers 55 (2014) 1, pp. 187-207

The penalized maximum likelihood estimator (PMLE) has been widely used for variable selection in high-dimensional data. Various penalty functions have been employed for this purpose, e.g., Lasso, weighted Lasso, or smoothly clipped absolute deviations. However, the PMLE can be very sensitive to...

Persistent link: https://www.econbiz.de/10010998632

A hybrid forecasting model based on outlier detection and fuzzy time series – A case study on Hainan wind farm of China

Wang, Jianzhou; Xiong, Shenghua - In: Energy 76 (2014) C, pp. 526-541

Wind energy is regarded as a worldwide renewable and alternative energy that can relieve the energy shortage, reduce environmental pollution, and provide a significant potential economic benefit. In this paper, a hybrid method is developed to properly and efficiently forecast the daily wind...

Persistent link: https://www.econbiz.de/10010939857

A distribution-free test for outliers

Candelon, Bertrand; Metiu, Norbert - Deutsche Bundesbank - 2013

Determining whether a data set contains one or more outliers is a challenge commonly faced in applied statistics. This paper introduces a distribution-free test for multiple outliers in data drawn from an unknown data generating process. Besides, a sequential algorithm is proposed in order to...

Persistent link: https://www.econbiz.de/10010957131

Extreme Value Theory Filtering Techniques for Outlier Detection

Olmo, J. - Department of Economics, City University - 2009

We introduce asymptotic parameter-free hypothesis tests based on extreme value theory to detect outlying observations in finite samples. Our tests have nontrivial power for detecting outliers for general forms of the parent distribution and can be implemented when this is unknown and needs to be...

Persistent link: https://www.econbiz.de/10011268975

Methods for Measuring the Effects of the EU Presidency on International Tourism

Smeral, Egon; Wüger, Michael - Österreichisches Institut für Wirtschaftsforschung (WIFO) - 2006

This study uses time-series techniques and econometric approaches in order to quantify the effects that organising an EU presidency has on the tourism exports of a country. The approach to explain tourism revenues by a time-series intervention model filters out special effects (data...

Persistent link: https://www.econbiz.de/10005020372

Outlier Detection in GARCH Models

Doornik, Jurgen A.; Ooms, Marius - Tinbergen Institute - 2005

We present a new procedure for detecting multiple additive outliers in GARCH(1,1) models at unknown dates. The outlier candidates are the observations with the largest standardized residual. First, a likelihood-ratio based test determines the presence and timing of an outlier. Next, a second...

Persistent link: https://www.econbiz.de/10005144394

A Simple Diagnostic Plot Connecting Robust Estimation, Outlier Detection, and False Discovery Rates

Rice, Kenneth; Spiegelhalter, David - In: Journal of Applied Statistics 33 (2006) 10, pp. 1131-1147

Robust estimation of parameters, and identification of specific data points that are discordant with an assumed model, are often treated as different statistical problems. The two aims are, however, closely inter-related and in many cases the two analyses are required simultaneously. We present...

Persistent link: https://www.econbiz.de/10009225460

Estimation of Commodity Specific Production Costs Using German Farm Accountancy Data

Bahta, Sirak Teclemariam; Berner, Anja; Offermann, Frank - European Association of Agricultural Economists - EAAE - 2011

A central problem in estimating per unit costs of production originates from the fact that most farms produce multiple outputs and standard farm-accounting data are only available at the whole-farm level. The seemingly unrelated regression (SUR) approach is used to estimate per unit production...

Persistent link: https://www.econbiz.de/10009326141

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