Browsing by Author "Nicolis, Orietta"

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    A special issue on: Statistical methods in mining industry
    (2018) Nicolis, Orietta; Pascual Jiménez, Rodrigo
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    Influence diagnostics in Gaussian spatial-temporal linear models with separable covariance
    (2023) Saavedra Nievas, Juan Carlos; Nicolis, Orietta; Galea Rojas, Manuel Jesús; Ibacache Pulgar, German
    In recent decades, there has been a growing interest in modeling spatial-temporal data, which can be found in many fields including geoscience, meteorology and ecology, among many others. The spatial-temporal dependence structure modeling, using a random field approach, is an indispensable tool to estimate the parameters that define this structure. However, this estimation may be greatly affected by the presence of atypical observations in the sampled data. Our proposal is to extend the results of Uribe-Opazo et al. (J Appl Stat 39:615-630, 2012) and De Bastiani et al. (Test 24:322-340, 2015) in the studies of diagnostic techniques to assess the sensitivity of the maximum likelihood estimators to small perturbations in the response variable for the spatial-temporal linear models with separable covariance. The method's viability is illustrated in a simulation study, and in an application to eggs anchovy (Engraulis ringens) abundance data in ichthyoplankton surveys from the northern zone of Chile. The results show that the proposed methodology allows to detect influential observations in a spatial-temporal data set when their covariances are separable.
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    Multi-Objective Location Problem for Bank Branches
    (2023) Montero, Elizabeth; Nicolis, Orietta; Reid, Samantha; Torres, Marcelo
    Although current technologies allow simple online banking transactions, it is vital to guarantee access to bank branches both for customers and businesses. Banking branch interactions improve trust in bank institutions in everyday situations and emergencies. This research addresses the problem of the location of banking facilities. A set of objective functions related to socio-economic variables, geographical coverage and bankers preferences are considered. A multi-objective linear programming model is proposed to solve different versions of the problem considering a maximum radial distance coverage. The (mono/bi/multi) objective versions of the problem are analyzed by varying the values of the weights of objective functions in the proposed model that is then solved using AMPL Gurobi solver. The case study is carried out in Santiago de Chile with data from a local banking institution. In the results, the bank's initial situation is analyzed to contrast the solutions found later. This analysis is performed considering the mono-objective, bi-objective, and multi-objective nature of the studied problem. In all these cases, we analyzed changes in the structure of solutions as the coverage of the branches increases. The proposed model can quickly obtain feasible solutions according to the needs and available resources, allowing to replicate the analysis in different institutions under similar conditions considering strategically established priorities.