000			02378nam a2200325 i 4500
001			500000933
003			UVAL
005			20240507115313.0
007			ta
008			170801s20162016chl g 000 0 spa d
040			_aDIBRA _bspa _cUVAL _erda
041	0		_aspa
084			_aM
100	0		_aHuerta Aguiar, Mauricio Hernán _9218908, _eauthor.
245	1	0	_aA beta partial least squares regression model : _bdiagnostics and application to mining data / _cMauricio Hernán Huerta Aguiar.
264		3	_aValparaíso, Chile : _bUniversidad de Valparaíso, _c2016
300			_a46 hojas.
502			_aMagíster en Estadística.
520			_aPartial least squares (PLS) regression is a multivariate technique developed to solve the problem of multicollinearity and/or high dimensionality related to explanatory variables in multiple linear regression. PLS regression has been widely applied assuming normality, but this assumption is often violated in different practical problems. Particularly, if the response variable follows an asymmetric distribution or it is bounded into an interval, normality should be discarded. For example, if this response variable is restricted to values between zero and one, a beta distribution is more suitable for PLS modeling than the normal distribution. We consider a beta PLS regression and its diagnostics for modeling the proportion of kaolinite, a clay mineral present in rocks which is measured by infrared spectroscopy with wavelengths. We propose a residual used in the generalized additive models for location scale and shape and the Cook and Mahalanobis distances as diagnostic tools for this model. We illustrate the proposed methodology with real-world mining data. The analyses and results provided in this study based on the beta PLS regression model and its diagnostics may be of interest for the Chilean mining sector and for the world mining industry.
650		0	_aANALISIS DE REGRESION.
650		0	_aDATOS ESTADISTICOS.
650		0	_aESTADISTICA.
700	1		_aLeiva Sánchez, Víctor E., _e, Profesor guía. _948320.
700	1		_aRiquelme, Marco, _e, Profesor guía. _998458.
710	0		_aUniversidad de Valparaíso. _b. Facultad de Ciencias. _b. Departamento de Estadística.
942			_c5 _2ddc
999			_c91122 _d91122