Search Results - subject:"Matrix norm"

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Global sensitivity analysis and robustness in linear programming using different norms

Hladík, Milan - In: Central European journal of operations research 33 (2025) 3, pp. 661-677

Persistent link: https://www.econbiz.de/10015549189

Classifying bounded rationality in limited data sets : a Slutsky matrix approach

Aguiar, Victor H.; Serrano, Roberto - In: SERIEs : Journal of the Spanish Economic Association 9 (2018) 4, pp. 389-421

Persistent link: https://www.econbiz.de/10011967450

Classifying bounded rationality in limited data sets: A Slutsky matrix approach

Aguiar, Victor H.; Serrano, Roberto - In: SERIEs - Journal of the Spanish Economic Association 9 (2018) 4, pp. 389-421

Given any observed finite sequence of prices, wealth, and demand choices, we propose a way to measure and classify the departures from rationality in a systematic fashion, by connecting violations of the underlying Slutsky matrix properties to the length of revealed demand cycles. The approach...

Persistent link: https://www.econbiz.de/10011994625

Principal Components and Factor Analysis. A Comparative Study.

Travaglini, Guido - Volkswirtschaftliche Fakultät, … - 2011

A comparison between Principal Component Analysis (PCA) and Factor Analysis (FA) is performed both theoretically and empirically for a random matrix X:(n x p) , where n is the number of observations and both coordinates may be very large. The comparison surveys the asymptotic properties of the...

Persistent link: https://www.econbiz.de/10009402055

On Loss Functions and Ranking Forecasting Performances of Multivariate Volatility Models

Laurent, Sébastien; Rombouts, Jeroen V.K.; Violante, … - Centre Interuniversitaire sur le Risque, les Politiques … - 2009

A large number of parameterizations have been proposed to model conditional variance dynamics in a multivariate framework. However, little is known about the ranking of multivariate volatility models in terms of their forecasting ability. The ranking of multivariate volatility models is...

Persistent link: https://www.econbiz.de/10008567826

On Loss Functions and Ranking Forecasting Performances of Multivariate Volatility Models

Laurent, Sébastien; Rombouts, Jeroen; Violente, Francesco - Centre Interuniversitaire de Recherche en Analyse des … - 2009

Persistent link: https://www.econbiz.de/10008574654

Consistent ranking of multivariate volatility models

LAURENT, Sebastien; ROMBOUTS, Jeroen V.K.; VIOLANTE, … - Center for Operations Research and Econometrics (CORE), … - 2009

A large number of parameterizations have been proposed to model conditional variance dynamics in a multivariate framework. This paper examines the ranking of multivariate volatility models in terms of their ability to forecast out-of-sample conditional variance matrices. We investigate how...

Persistent link: https://www.econbiz.de/10008550212

Moments tensors, Hilbert's identity, and k-wise uncorrelated random variables

Jiang, Bo; He, Simai; Li, Zhening; Zhang, Shuzhong - In: Mathematics of operations research 39 (2014) 3, pp. 775-788

Persistent link: https://www.econbiz.de/10010402957

A unified algorithm for mixed <InlineEquation ID="IEq1"> <EquationSource Format="TEX">$$l_{2,p}$$</EquationSource> <EquationSource Format="MATHML"> <math xmlns:xlink="http://www.w3.org/1999/xlink"> <msub> <mi>l</mi> <mrow> <mn>2</mn> <mo>,</mo> <mi>p</mi> </mrow> </msub> </math> </EquationSource> </InlineEquation>-minimizations and its application in feature selection

Wang, Liping; Chen, Songcan; Wang, Yuanping - In: Computational Optimization and Applications 58 (2014) 2, pp. 409-421

Recently, matrix norm <InlineEquation ID="IEq4"> <EquationSource Format="TEX">$$l_{2,1}$$</EquationSource …> matrix norm is often used to find jointly sparse solution. Actually, computational studies have showed that the solution of …="false">]</mo> </mrow> <mo stretchy="false">)</mo> </mrow> </mrow> </math> </EquationSource> </InlineEquation> matrix norm which is non …

Persistent link: https://www.econbiz.de/10010998363

Graph Partitioning by Correspondence Analysis and Taxicab Correspondence Analysis

Choulakian, Vartan; Tibeiro, Jules - In: Journal of Classification 30 (2013) 3, pp. 397-427

We consider correspondence analysis (CA) and taxicab correspondence analysis (TCA) of relational datasets that can mathematically be described as weighted loopless graphs. Such data appear in particular in network analysis. We present CA and TCA as relaxation methods for the graph partitioning...

Persistent link: https://www.econbiz.de/10010848617