%% $Id$
@Book{TESL2013,
  author =	 {T. Hastie and J. Friedman and R. Tibshirani},
  title =	 {The Elements of Statistical Learning: data mining,
                  inference, and prediction},
  publisher =	 {Springer},
  year =	 2013,
  note =	 {10th printing with corrections}
}

@Article{Voet1994,
  author =	 {H. van der Voet},
  title =	 {Comparing the predictive accuracy of models using a
                  simple randomization test},
  journal =	 {Chemom. Intell. Lab. Syst.},
  year =	 1994,
  volume =	 25,
  number =	 2,
  pages =	 {313--323}
}

@Article{ Kresta1991,
	title = "Multivariate Statistical Monitoring of Process Operating Performance",
	author = "J.V. Kresta and J.F. MacGregor and T.E. Marlin",
	journal = "The Canadian Journal of Chemical Engineering",
	volume = "69",
	pages = "35--47",
	number = "1",
	year = "1991"
}

@Article{ McIntosh1996,
	title = "Spatial Pattern Analysis of Functional Brain Images using Partial Least Squares ",
	author = "A.R. McIntosh and F.L. Bookstein and J.V. Haxby and C.L. Grady",
	journal = "Neuroimage",
	pages = "143--157",
	volume = "3",
	number = "3",
	year = "1996"
}

@Article{ Nguyen2002,
	author = "D.V. Nguyen and D.M. Rocke",
	title = "Tumor Classification by Partial Least Squares using Microarray Gene Expression Data",
	journal = "Bioinformatics",
	pages = "39--50",
	year = "2002",
	volume = "18",
	number = "1"
}

@Article{ Fornell1982,
	title = "Two Structural Equation Models -- {LISREL} and {PLS} Applied to Consumer-Exit Voice Theory ",
	author = "C. Fornell and F.L. Bookstein",
	journal = "Journal of Marketing Research",
	pages = "440--452",
	volume = "19",
	number = "4",
	year = "1982"
}

@Article{ Cramer1988,
	title = "Comparative Molecular-Field Analysis ({ComFA}). 1. {Effect} of Shape on Binding of Steroids to Carrier Proteins",
	author = "R.D. Cramer and D.E. Patterson and J.D. Bunce",
	journal = "Journal of the American Chemical Society",
	pages = "5959--5967",
	volume = "110",
	number = "18",
	year = "1988"
}

@Book{ TESL,
	title = "The Elements of Statistical Learning",
	editor = "T. Hastie and R. Tibshirani and J.H. Friedman",
	publisher = "Springer",
	address = "New York",
	year = "2001"
}

@Article{ Geladi1985, 
        title = "Linearization and Scatter-Correction for {NIR} Reflectance
                  Spectra of Meat",   
        author = "P. Geladi and D. MacDougall and H. Martens", 
        journal = "Applied Spectroscopy",
        volume = "39",
        year = "1985",
        pages = "491--500"
}

@Article{ Frank1993,
        author = {Frank, Ildiko E. and Friedman, Jerome H.},
        title = {A Statistical View of Some Chemometrics Regression Tools (with Discussion)},
        journal = {Technometrics},
        volume = {35},
        number = {2},
        pages = {109--148},
        keywords = {multiple response regression
partial least squares
principal components regression
ridge regression
variable subset selection},
        year = {1993}
}

@Article{ Martens2001,
	title = "Reliable and Relevant Modelling of Real World Data: a Personal Account of the Development of {PLS} Regression",
	author = "H. Martens",
	journal = "Chemometrics and Intelligent Laboratory Systems",
	pages = "85--95",
	volume = "58",
	number = "2",
	year = "2001"
}

@Article{ Wold2001,
	title = "Personal Memories of the Early {PLS} Development",
	author = "S. Wold",
	journal = "Chemometrics and Intelligent Laboratory Systems",
	pages = "83--84",
	volume = "58",
	number = "2",
	year = "2001"
}

@article{ Jong1993a,
        author = {de Jong, Sijmen},
        title = {{SIMPLS}: an Alternative Approach to Partial Least Squares Regression},
        journal = {Chemometrics and Intelligent Laboratory Systems},
        volume = {18},
        pages = {251--263},
        year = {1993}
}

@BOOK{R:Chambers+Hastie:1992,
  AUTHOR = {John M. Chambers and Trevor J. Hastie},
  TITLE = {Statistical Models in {S}},
  PUBLISHER = {Chapman \& Hall},
  YEAR = 1992,
  ADDRESS = {London},
  PUBLISHERURL = {http://www.crcpress.com/shopping_cart/products/product_detail.asp?sku=C3040&parent_id=&pc=},
  ABSTRACT = {This is also called the ``\emph{White Book}'', and
                  introduced S version 3, which added structures to
                  facilitate statistical modeling in S.},
  ORDERINFO = {crcpress.txt}
}

@article{SwiWeiWijBuy_StrConRobMulCalMod,
        author = {Swierenga, H. and de Weijer, A. P. and van Wijk, R. J. and Buydens, L. M. C.},
        title = {Strategy for Constructing Robust Multivariate Calibration Models},
        journal = {Chemometrics and Intelligent Laboratory Systems},
        year = {1999},
        volume = {49},
        number = {1},
        pages = {1--17}
}

@book{Mas_etal_HandChemQualB,
        author = {Massart, D. L. and Vandeginste, B. G. M. and Buydens, L. M. C. and de Jong, S. and Lewi, P. J. and Smeyers-Verbeke, J.},
        title = {Handbook of Chemometrics and Qualimetrics: Part B},
        publisher = {Elsevier},
        year = {1998}
}

@article{LacMic:EstERRDA,
	author = {Lachenbruch, Peter A. and Mickey, M. Ray},
	title = {Estimation of Error Rates in Discriminant Analysis},
	journal = {Technometrics},
	volume = {10},
	number = {1},
	pages = {1--11},
	kommentar = {har papir},
	year = {1968}
}

@article{Kal:2DatNIR,
	author = {Kalivas, John H.},
	title = {Two Data Sets of Near Infrared Spectra},
	journal = {Chemometrics and Intelligent Laboratory Systems},
	volume = {37},
	pages = {255--259},
	kommentar = {har papir},
	keywords = {near infrared spectroscopy
wheat
protein
moisture
octane number
wavelength selection
cyclic subspace regression
principal component regression
partial least squares},
	year = {1997}
}

@article{MevCed:MSEPest,
	author = {Mevik, Bjørn-Helge and Cederkvist, Henrik René},
	title = {Mean Squared Error of Prediction {(MSEP)} Estimates for Principal Component Regression {(PCR)} and Partial Least Squares Regression {(PLSR)}},
	journal = {Journal of Chemometrics},
	volume = {18},
	number = {9},
	pages = {422--429},
	kommentar = {har pdf-fil},
	abstract = {This paper presents results from simulations based on real data, comparing several competing mean squared error of prediction (MSEP) estimators on principal component regression (PCR) and partial least squares regression (PLSR): leave-one-out cross-validation, K-fold and adjusted K-fold cross-validation, the ordinary bootstrap estimate, the bootstrap smoothed cross-validation (BCV) estimate and the 0.632 bootstrap estimate. The overall performance of the estimators is compared in terms of their bias, variance and squared error. The results indicate that the 0.632 estimate and leave-one-out cross-validation are preferable when one can afford the computation. Otherwise adjusted 5- or 10-fold cross-validation are good candidates because of their computational efficiency.},
	keywords = {mean squared error of prediction (MSEP)
cross-validation
adjusted cross-validation
bootstrap
0.632 estimate
principal component regression (PCR)
partial least squares regression (PLSR)},
	year = {2004}
}

@article{DayMacGre:ImprPlsAlg,
	author = {Dayal, B. S. and MacGregor, J. F.},
	title = {Improved PLS algorithms},
	journal = {Journal of Chemometrics},
	volume = {11},
	number = {1},
	pages = {73-85},
	kommentar = {har papir},
	abstract = {In this paper a proof is given that only one of either the X- or the Y-matrix in PLS algorithms needs to be deflated during the sequential process of computing latent vectors. With the aid of this proof the original kernel algorithm developed by Lindgren et al. (J. Chemometrics, 7, 45 (1993)) is modified to provide two faster and more economical algorithms. The performances of these new algorithms are compared with that of De Jong and Ter Braak's (J. Chemometrics, 8, 169 (1994)) modified kernel algorithm in terms of speed and the new algorithms are shown to be much faster. A very fast kernel algorithm for updating PLS models in a recursive manner and for exponentially discounting past data is also presented. (C) 1997 by John Wiley & Sons, Ltd.},
	keywords = {partial least squares (PLS), algorithms, faster kernel algorithms, recursive PLS, exponentially weighted PLS
kernel algorithm},
	year = {1997}
}

@book{MarNaes:MultCal,
	author = {Martens, Harald and Næs, Tormod},
	title = {Multivariate Calibration},
	publisher = {Wiley},
	address = {Chichester},
	kommentar = {har papir},
	year = {1989}
}

@article{MevWeh:plsJSS,
	author = {Mevik, Bjørn-Helge and Wehrens, Ron},
	title = {The {pls} package: Principal Component and Partial Least Squares Regression in {R}},
	journal = {Journal of Statistical Software},
	volume = {18},
	number = {2},
	pages = {1--24},
	year = {2007}
}

@article{indahl1999multivariate,
  title={Multivariate strategies for classification based on NIR-spectra—with application to mayonnaise},
  author={Indahl, Ulf G and Sahni, Narinder S and Kirkhus, Bente and N{\ae}s, Tormod},
  journal={Chemometrics and Intelligent Laboratory Systems},
  volume={49},
  number={1},
  pages={19--31},
  year={1999},
  publisher={Elsevier}
}

@article{indahl2009canonical,
  title={Canonical partial least squares—a unified PLS approach to classification and regression problems},
  author={Indahl, Ulf G and Liland, Kristian Hovde and N{\ae}s, Tormod},
  journal={Journal of Chemometrics: A Journal of the Chemometrics Society},
  volume={23},
  number={9},
  pages={495--504},
  year={2009},
  publisher={Wiley Online Library}
}
