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2010
Within disaggregation–aggregation approach, ordinal regression aims at inducing parameters of a preference model, for example, parameters of a value function, which represent some holistic preference comparisons of alternatives given by the Decision Maker (DM).
Greco, Salvatore +3 more
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Within disaggregation–aggregation approach, ordinal regression aims at inducing parameters of a preference model, for example, parameters of a value function, which represent some holistic preference comparisons of alternatives given by the Decision Maker (DM).
Greco, Salvatore +3 more
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2022
This thesis was scanned from the print manuscript for digital preservation and is copyright the author. Researchers can access this thesis by asking their local university, institution or public library to make a request on their behalf. Monash staff and postgraduate students can use the link in the References field.
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This thesis was scanned from the print manuscript for digital preservation and is copyright the author. Researchers can access this thesis by asking their local university, institution or public library to make a request on their behalf. Monash staff and postgraduate students can use the link in the References field.
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Robust regression through robust covariances
Communications in Statistics - Theory and Methods, 1986This paper discusses the estimation of regression parameters after summarizing the data by a covariance matrix of the concatenated vector of explanatory variables and response variable. A robust estimate of the covariance matrix leads to a robust regression estimator.
Ricardo Maronna, Stephan Morgenthaler
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Robust Principal Components Regression
2002We consider the multivariate linear regression model with p explanatory variables X and q ≥ 1 response variables Y. Moreover we assume that the regressors are multicollinear. This situation often occurs in the calibration of chemometrical data, where the X-variables correspond with spectra that are measured at many frequencies.
Verboven, Sabine, Hubert, Mia
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Robust regression: An introduction
Analytical Methods, 2012Analytical scientists use regression methods in two main areas. Calibration graphs are used with the results of instrumental analyses to obtain concentrations from test samples. Graphical methods are used to evaluate the results obtained when two methods, often a novel one and a reference one, are compared by applying them to the same set of test ...
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Bootstrapping robust regression
1992In the last chapter we have made extensive use of the simple (linear) structure of the model and of the estimate. As an example of a more complicated estimator we study in this chapter bootstrap of M-estimates \(\hat \beta \)in linear models. As in the last chapter for each n we consider the linear model $$ \begin{array}{*{20}{c}} {{Y_i} = X_i^T ...
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