7 documents found, page 1 of 1
Comparing the inertial effect of MEWMA and multivariate sliding window schemes ...
Moraes, D. A. O.; Oliveira, Fernando Luiz Pereira de; Duczmal, Luiz Henrique; Cruz, Frederico Rodrigues Borges daIn practical applications of multivariate sliding window (SW) control charts, a considerable amount of difficulty lies in selecting parameters related to the window size and to the disposal of past observations. Although widely used for pattern recognition problems, to the best of the authors’ knowledge, there have been no comparative analyses of the efficiencies of multivariate SW schemes and more traditional ...
Self-oriented control charts for efficient monitoring of mean vectors.
Moraes, D. A. O.; Oliveira, Fernando Luiz Pereira de; Quinino, Roberto da Costa; Duczmal, Luiz HenriqueThis work presents a procedure for monitoring the centre of multivariate processes by optimising the noncentrality parameter with respect to the maximum separability between the in- and out-of-control states. Similarly to the Principal Component Analysis, this procedure is a linear transformation but using a different criterion which maximises the trace of two scatter matrices. The proposed linear statistic is ...
Penalized likelihood and multi-objective spatial scans for the detection and in...
Cançado, André Luiz Fernandes; Duarte, Anderson Ribeiro; Duczmal, Luiz Henrique; Ferreira Neto, Sabino José; Fonseca, Carlos M.; Gontijo, Eliane DiasBackground: Irregularly shaped spatial clusters are difficult to delineate. A cluster found by an algorithm often spreads through large portions of the map, impacting its geographical meaning. Penalized likelihood methods for Kulldorff’s spatial scan statistics have been used to control the excessive freedom of the shape of clusters. Penalty functions based on cluster geometry and non-connectivity have been pro...
Nonparametric intensity bounds for the delineation of spatial clusters
Oliveira, Fernando Luiz Pereira de; Duczmal, Luiz Henrique; Cançado, André Luiz Fernandes; Tavares, RicardoThe authors were partially supported by the Brazilian institutions CAPES, CNPq and Fapemig.; Background: There is considerable uncertainty in the disease rate estimation for aggregated area maps, especially for small population areas. As a consequence the delineation of local clustering is subject to substantial variation. Consider the most likely disease cluster produced by any given method, like SaTScan, for ...
Data-driven inference for the spatial scan statistic.
Almeida, Alexandre Celestino Leite de; Duarte, Anderson Ribeiro; Duczmal, Luiz Henrique; Oliveira, Fernando Luiz Pereira deBackground: Kulldorff’s spatial scan statistic for aggregated area map s searches for cluster s of case s without specifying their size (numb er of areas) or geo graphic location in advance . Their statistical significance is tested while adjusting for the multiple testing inherent in such a procedure. However, as is shown in this work, this adjustment is not don e in an even manner for all possible cluster siz...
Penalized likelihood and multi-objective spatial scans for the detection and in...
Cançado, André Luiz Fernandes; Duarte, Anderson Ribeiro; Duczmal, Luiz Henrique; Ferreira, Sabino José; Fonseca, Carlos M.; Gontijo, Eliane DiasBackground: Irregularly shape d spatial clusters are difficult to delineate. A cluster found by an algorithm often spreads through large portions of the map, impacting its geographical meaning. Penalized likelihood methods for Kulldorff’ s spatial scan statistics have been used to control the excessive freedom of the shape of clusters . Penalty functions based on cluster geometry and non-connectivity have been ...
Nonparametric intensity bounds for the delineation of spatial clusters.
Oliveira, Fernando Luiz Pereira de; Duczmal, Luiz Henrique; Cançado, André Luiz Fernandes; Tavares, RicardoBackground: There is considerable uncertainty in the disease rate estimation for aggregated area maps, especially for small population areas. As a consequence the delineation of local clustering is subject to substantial variation. Consider the most likely disease cluster produced by any given method, like SaTScan, for the detection and inference of spatial clusters in a map divided into areas; if this cluster ...