DSpace Collection:
http://hdl.handle.net/2099/3720
Thu, 29 Jan 2015 16:22:00 GMT2015-01-29T16:22:00Zwebmaster.bupc@upc.eduUniversitat Politècnica de Catalunya. Servei de Biblioteques i DocumentaciónoPartial cooperation and convex sets
http://hdl.handle.net/2099/3739
Title: Partial cooperation and convex sets
Authors: Romero García, J. Enrique; López Vázquez, Jorge J.
Abstract: We consider games of transferable utility, those that deal with partial cooperation situations, made up of coalition systems, in which every unit coalition is feasible and every coalition of players can be expressed as a disjoint union of maximal feasible coalitions. These systems are named partition
systems and cause restricted games. To sum up, we study feasible coalition systems defined by a partial order designed for a set of players and we analyze the characteristics of a feasible coalition
system developed from a family of convex sets.Wed, 01 Jan 2003 00:00:00 GMThttp://hdl.handle.net/2099/37392003-01-01T00:00:00ZRomero García, J. Enrique; López Vázquez, Jorge J.noOperations research, Mathematical programmingWe consider games of transferable utility, those that deal with partial cooperation situations, made up of coalition systems, in which every unit coalition is feasible and every coalition of players can be expressed as a disjoint union of maximal feasible coalitions. These systems are named partition
systems and cause restricted games. To sum up, we study feasible coalition systems defined by a partial order designed for a set of players and we analyze the characteristics of a feasible coalition
system developed from a family of convex sets.On two matrix derivatives by Kollo and von Rosen
http://hdl.handle.net/2099/3738
Title: On two matrix derivatives by Kollo and von Rosen
Authors: Neudecker, Heinz
Abstract: The article establishes relationships between the matrix derivatives of Fwith respect to Xas introduced by von Rosen (1988), Kollo and von Rosen (2000) and the Magnus-Neudecker (1999) matrix derivative.
The usual transformations apply and the Moore-Penrose inverse of the duplication matrix is used. Both Xand F have the same dimension.Wed, 01 Jan 2003 00:00:00 GMThttp://hdl.handle.net/2099/37382003-01-01T00:00:00ZNeudecker, HeinznoMultivariate analysis, Algebras, Linear, Multilinear algebra, MatricesThe article establishes relationships between the matrix derivatives of Fwith respect to Xas introduced by von Rosen (1988), Kollo and von Rosen (2000) and the Magnus-Neudecker (1999) matrix derivative.
The usual transformations apply and the Moore-Penrose inverse of the duplication matrix is used. Both Xand F have the same dimension.Asymptotic study of canonical correlation analysis: from matrix and analytic approach to operator and tensor approach
http://hdl.handle.net/2099/3737
Title: Asymptotic study of canonical correlation analysis: from matrix and analytic approach to operator and tensor approach
Authors: Fine, Jeanne
Abstract: Asymptotic study of canonical correlation analysis gives the opportunity to present the different steps of an asymptotic study and to show the interest of an operator and tensor approach of multidimensional
asymptotic statistics rather than the classical, matrix and analytic approach. Using the last approach, Anderson (1999) assumes the random vectors to have a normal distribution and the non zero canonical
correlation coefficients to be distinct. The new approach we use, Fine (2000), is coordinate-free,distribution-free and permits to have no restriction on the canonical correlation coefficients multiplicity order. Of course, when vectors have a normal distribution and when the non zero canonical correlation coefficients are distinct, it is possible to find again Anderson’s results but we diverge on two of them.
In this methodological presentation, we insist on the analysis frame (Dauxois and Pousse, 1976), the
sampling model (Dauxois, Fine and Pousse, 1979) and the different mathematical tools (Fine, 1987,
Dauxois, Romain and Viguier, 1994) which permit to solve problems encountered in this type of study,
and even to obtain asymptotic behavior of the analyses random elements such as principal components
and canonical variables.)Wed, 01 Jan 2003 00:00:00 GMThttp://hdl.handle.net/2099/37372003-01-01T00:00:00ZFine, JeannenoDistribution (Probability theory), Multivariate analysis, Operator theoryAsymptotic study of canonical correlation analysis gives the opportunity to present the different steps of an asymptotic study and to show the interest of an operator and tensor approach of multidimensional
asymptotic statistics rather than the classical, matrix and analytic approach. Using the last approach, Anderson (1999) assumes the random vectors to have a normal distribution and the non zero canonical
correlation coefficients to be distinct. The new approach we use, Fine (2000), is coordinate-free,distribution-free and permits to have no restriction on the canonical correlation coefficients multiplicity order. Of course, when vectors have a normal distribution and when the non zero canonical correlation coefficients are distinct, it is possible to find again Anderson’s results but we diverge on two of them.
In this methodological presentation, we insist on the analysis frame (Dauxois and Pousse, 1976), the
sampling model (Dauxois, Fine and Pousse, 1979) and the different mathematical tools (Fine, 1987,
Dauxois, Romain and Viguier, 1994) which permit to solve problems encountered in this type of study,
and even to obtain asymptotic behavior of the analyses random elements such as principal components
and canonical variables.)A posteriori disclosure risk measure for tabular data based on conditional entropy
http://hdl.handle.net/2099/3736
Title: A posteriori disclosure risk measure for tabular data based on conditional entropy
Authors: Oganian, Anna; Domingo Ferrer, Josep
Abstract: Statistical database protection, also known as Statistical Disclosure Control (SDC), is a part of information security which tries to prevent published statistical information (tables, individual records)from disclosing the contribution of specific respondents. This paper deals with the assessment of the
disclosure risk associated to the release of tabular data. So-called sensitivity rules are currently being used to measure the disclosure risk for tables. These rules operate on an a priori basis: the data are
examined and the rules are used to decide whether the data can be released as they stand or should rather be protected. In this paper, we propose to complement a priori risk assessment with a posteriori risk assessment in order to achieve a higher level of security, that is, we propose to take the protected information into account when measuring the disclosure risk. The proposed a posteriori disclosure risk measure is compatible with a broad class of disclosure protection methods and can be extended for computing disclosure risk for a set of linked tables. In the case of linked table protection via cell suppression, the proposed measure allows detection of
secondary suppression patterns which offer more protection than others.Wed, 01 Jan 2003 00:00:00 GMThttp://hdl.handle.net/2099/37362003-01-01T00:00:00ZOganian, Anna; Domingo Ferrer, JosepnoStatisticsStatistical database protection, also known as Statistical Disclosure Control (SDC), is a part of information security which tries to prevent published statistical information (tables, individual records)from disclosing the contribution of specific respondents. This paper deals with the assessment of the
disclosure risk associated to the release of tabular data. So-called sensitivity rules are currently being used to measure the disclosure risk for tables. These rules operate on an a priori basis: the data are
examined and the rules are used to decide whether the data can be released as they stand or should rather be protected. In this paper, we propose to complement a priori risk assessment with a posteriori risk assessment in order to achieve a higher level of security, that is, we propose to take the protected information into account when measuring the disclosure risk. The proposed a posteriori disclosure risk measure is compatible with a broad class of disclosure protection methods and can be extended for computing disclosure risk for a set of linked tables. In the case of linked table protection via cell suppression, the proposed measure allows detection of
secondary suppression patterns which offer more protection than others.