Listar por autoría "07ab5f2b-6e4d-4f11-b67e-9a97768f392a"
Mostrando ítems 1-12 de 12
-
A spatial randomness test based on the box-counting dimension
Springer (2022)Statistical modelling of a spatial point pattern often begins by testing the hypothesis of spatial randomness. Classical tests are based on quadrat counts and distance-based methods. Alternatively, we propose a new statistical ... -
A universal kriging approach for spatial functional data
Springer (2013-02)In a wide range of scientific fields the outputs coming from certain measurements often come in form of curves. In this paper we give a solution to the problem of spatial prediction of non-stationary functional data. We ... -
Analysis of variance for spatially correlated functional data: Application to brain data
Elsevier (2019)Functional data showing spatial dependence structure occur in many applied fields. For example, in meteorology when curves of temperature are obtained in a monitoring network, or in neurological studies when curves of the ...
-
Geofd: An R Package for Function-Valued Geostatistical Prediction
Universidad Nacional de Colombia (2015-12)Spatially correlated curves are present in a wide range of applied disciplines. In this paper we describe the R package geofd which implements ordinary kriging prediction for this type of data. Initially the curves ...
-
Hierarchical clustering of spatially correlated functional data
John Wiley & Sons (2012-11)Classification problems of functional data arise naturally in many applications. Several approaches have been considered for solving the problem of funding groups based on functional data. In this paper we are interested ...
-
High leverage detection in general functional regression models with spatially correlated errors
Wiley (2021)The presence of curves that deviate markedly from the core of a set of curves can greatly affect inference and forecasting in a functional regression model. Thus their detection is key to increase the accuracy of the ...
-
Kriging with external drift for functional data for air quality monitoring
Springer Verlag (2014-07)Functional data featured by a spatial dependence structure occur in many environmental sciences when curves are observed, for example, along time or along depth. Recently, some methods allowing for the prediction of a curve ...
-
Multivariate functional random fields: prediction and optimal sampling
Springer Verlag (2017)This paper develops spatial prediction of a functional variable at unsampled sites, using functional covariates, that is, we present a functional cokriging method. We show that through the representation of each function ...
-
On the performance of two clustering methods for spatial functional data
Springer Verlag (2015-10)The performance of two clustering strategies for spatially correlated functional data based on the same measure of spatial dependence is examined and compared. In particular, the role of the spatial dependence computed by ...
-
Optimal dynamic spatial sampling
John Wiley & Sons Ltd (2016)This paper provides new tools for dynamic spatial sampling designs to find the optimal spatial mean estimation and the optimal spatial prediction, based on the temporal variation of the spatial dependence structure. We ...
-
Residual kriging for functional data. Application to the spatial prediction of salinity curves
Taylor & Francis (2015)Recently several methodologies for carrying out geostatistical analysis of functional data has been proposed. All of them assume that the spatial functional process considered is stationary. However in practice we often ...
-
Statistics for spatial functional data: some recent contributions
John Wiley & Sons, Ltd. (2010)Functional data analysis (FDA) is a relatively new branch in statistics. Experiments where a complete function is observed for each individual give rise to functional data. In this work we focus on the case of functional ...
