000			02503nam a2200289 i 4500
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008			190625s2018 ||||| |||| 00| 0 eng d
040			_aDIBRA _bspa _cUVAL _erda
084			_aM
100	1		_9227150 _aMorales Oñate, Víctor Roberto, _eautor.
245	1	0	_aEuclidean likelihood method for space time covariance function using parallel computation / _cVíctor Roberto Morales Oñate.
264		1	_aValparaíso : _bUniversidad de Valparaíso, _c2018.
300			_a69 hojas.
336			_atext _btxt _2rdacontent
337			_aunmediated _bn _2rdamedia
338			_avolume _bnc _2rdacarrier
502			_6Doctor en Estadística.
520			_aToday, statistical analyses with one or more variables, observed in space and time are useful in different areas, such as environmental sciences and engineering to name a few. Random fields are the mathematical foundation for the statistical analyses of this kind of data which allows to describe their marginal behavior and to assess the dependence structure inside the data. Three fundamental steps are needed when analyzing such data using random fields: modeling, estimation and prediction. We focus on estimation. In particular, we develop estimation methods for spatio temporal Gaussian random fields observed on a large number of location sites and/or temporal instants. Maximum likelihood, in this case, is computationally unfeasible. This thesis elaborates an Euclidean likelihood method for space time covariance function using parallel computation in order to reduce the computation burden for the estimation of a spatio-temporal random field. The method is called STBEU which stands for space-time blockwise euclidean likelihood. The method was implemented in R and it was boosted using parallel computation with the OpenCL framework. An R package called STBEU was created for reproducibility purposes. We also study the asymptotic properties of the method and show, through numerical simulation and real data-set estimation, that STBEU offer a good balance between statistical efficiency and computation complexity.
650		4	_aDISTRIBUCION ASINTOTICA (TEORIA DE LAS PROBABILIDADES) _971177.
650		4	_985164 _aANALISIS DE COVARIANZA.
700	1		_aCrudu, Federico _9228610.
700	1		_aBevilacqua, Moreno, _eSupervisor _9204115.
710	2		_aUniversidad de Valparaíso (Chile). _bFacultad de Ciencias. _bCarrera de Ingeniería en Estadística _9205308.
942			_2ddc _c5
999			_c105302 _d105302