9 Bibliografía

Introducción a R: https://www.datacamp.com/courses/introduccion-a-r/?tap_a=5644-dce66f&tap_s=10907-287229

Achim Zeileis, Torsten Hothorn (2002). Diagnostic Checking in Regression Relationships. R News 2 (3), 7-10. URL http://CRAN.R-project.org/doc/Rnews/

Albright,R., Lerman,S. y Manski,C. (1977), “Development Of An Estimation Program For The M. Probit Model”. Federal Highway Administration

Akaike, H. (1974), “A new look at the statistical model identification”, IEEE Transactions on Automatic Control AC-19, pp. 716–723.

Amemiya, T. (1978), “On A Two-Step Estimation Of A Multivariate Logit Model”, Journal Of Econometrics 8.

Ashley, Richard A. (1984), “A Simple Test for Regression Parameter Instability,” Economic Inquiry 22, No. 2, 253-267.

Aznar, A. y Trívez, F. J. (1993), Métodos de Predicción en Economía II: Análisis de Series Temporales, Ed. Ariel.

Bassmann, R. (1957). “A Generalized Classical Method Of Linear Estimation Of Coefficients In A Structural Equation.” Econometrica 25, pp. 77-83

Beltran, Mauricio (2015): “Diseño e implementación de un nuevo clasificador de préstamos bancarios a través de minería de datos”. Tesis Doctoral. Departamento de Economía Aplicada y Estadística. UNED.

Breiman, L. (1996). “Bagging predictors”. Machine Learning 24 (2): 123–140. doi:10.1007/BF00058655. CiteSeerX: http://link.springer.com/article/10.1007%2FBF00058655

Breiman, L., Friedman, J. H., Olshen, R. A., and Stone, C. J. (1984). Classification and Regression Trees. Chapman & Hall/CRC.

Cayuela L (2010) Modelos lineales generalizados (GLM). EcoLab, Centro Andaluz de Medio Ambiente, Universidad de Granada. Junio 2010.

Durbin, J. y Koopman, S. J. (2001), Time Series Analysis by State Space Models (Oxford Statistical Science Series, nº 24), Oxford University Press.

Durbin, J. y Watson, G. S. (1950), “Testing for Serial Correlation Least Squares Regressions”, Biometrika, vol 37. pp. 409-428.

Engle, Robert F. (1974), Band Spectrum Regression,International Economic Review 15,1-11.

Bradley Efron, Elizabeth Halloran, and Susan Holmes (1996). “Bootstrap confidence levels for phylogenetic  trees”. PNAS 93 (23): http://www.pnas.org/content/93/23/13429.full.pdf

Fisher, R. A. (1936). “The Use of Multiple Measurements in Taxonomic Problems”. Annals of Eugenics 7 (2): 179–188.

Fix, E.; J.L. Hodges (1989) “(1951): An Important Contribution to Nonparametric Discriminant Analysis and Density Estimation: Commentary on Fix and Hodges (1951)”. International Statistical Review / Revue Internationale de Statistique 57 (3): 233-238.

Freund, Y; Schapire, R (1997); A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting, Journal of Computer and System Sciences, 55(1):119-139. http://cseweb.ucsd.edu/~yfreund/papers/adaboost.pdf

Fukunaga y Kessell (1973): “Nonparametric Bayes error estimation using unclassified samples”. IEEE Transactions on Information Theory (Volume:19 , Issue: 4 ):434-440.

Gallant, A. R.(1981) “On the Bias in Flexible Functional Forms and an Essentially Unbiased Form.” J. Econometrics 15(1981):211-45.

Gallant, A. R.(1984) “The Fourier Flexible Form.” Amer. J. Agr. Econ. 66(1984):204-15

Goldfield, S. M. y Quandt, R. E. (1965), “Some test for Homocedasticy”, Journal of American Statistical Association. Vol 37. pp 539-547.

Greene, W. H. (2000), Análisis Econométrico, Ed. Prentice Hall

Gujarati, D. (1997), Basic Econometrics, McGraw-Hill

Gujarati, D. (2003), Econometría, Ed. McGraw-Hill

Hair, J.F., Anderson R.E., Tatham R.L., Black W.C. (2008): Análisis Multivariante. 5ª Edición. Pearson, Prentice Hall.

Hastie, T., Tibshirani R. and Friedman, J. (2008), The Element of Statistical Learning. Data Minining, Inference and Prediction. Second Edition. Springe.

Hastings W- K. (1970), Monte Carlo Sampling Methods Using Markov Chains and Their Applications.Biometrika, Vol. 57, No. 1. (Apr., 1970), pp. 97-109.

Harvey, A.C. (1978), Linear Regression in the Frequency Domain, International Economic Review, 19, 507-512.

Hosmer, D. W., Jr., and S. Lemeshow (1980). Goodness-of-fit tests for the multiple logistic regression model. Communications in Statistics—Theory and Methods 9:1043–1069.

Johnston, J. (1997), Econometric Methods. McGraw-Hill.

Johnston, J. y Dinardo, J. (2001), Métodos De Econometría, Ed. Vicens-Vives 3ª Ed.

Loh, W.-Y. and Shih, Y.-S. (1997). Split selection methods for classification trees, Statistica Sinica 7: 815–840.

Mantegna, R. N.(1997): Degree of Correlation Inside a Financial Market in [Proc. of the ANDM 97 International Conference], Edited by J. Kadtke, AIP press.

Metropolis N., Rosenbluth A., Rosenbluth M., Teller A., and Teller E. (1953), Equations of state calculations by fast computing machines.J. Chem. Phys. 21, 1087{1091.

Mood, A. M. (1950), Introduction to the Theory of Statistics, McGraw-Hill.

Morgan J. N., Sonquist J. A., 1963, Problems in the analysis of survey data, and a proposal, J. Am. Statistical Assoc., 58:415-434.

Muñoz A., Parra F. (2007): Econometría Aplicada. Ediciones Académicas

Nelder, John; Wedderburn, Robert (1972). “Generalized Linear Models”. Journal of the Royal Statistical Society. Series A (General) (Blackwell Publishing) 135 (3): 370–384.

Newey WK, West KD (1987). “A Simple, Positive-Definite, Heteroskedasticity and Autocorrelation Consistent Covariance Matrix.” Econometrica, 55, 703–708.

Novales, A. (1993), Econometría, 2ª Edición, McGraw-Hill.

Parra, F.(2016): Econometria Aplicada I. https://econometria.files.wordpress.com/2014/11/parra-econometria-aplicada-i1.pdf

Parra, F.(2016): Econometria Aplicada II. https://econometria.files.wordpress.com/2015/01/parra-econometria-aplicada-ii5.pdf.

Parra, F. Vicente, J.A. (2019): Apuntes modulo3: Análisis de Datos Multivariantes I. Master de Data Science y Big Data aplicados a la Economía y a la Administración y Dirección de Empresas. UNED.

Pindyck, R. S. y Rubinfield, D. L. (1976), Econometric Models and Economic Forecast, McGraw-Hill.

Pindyck, R. S. y Rubinfield, D. L. (1980), Modelos Econométricos, Ed. Labor.

Pulido, A. (1983), Modelos Econométricos, Ed. Pirámide

Rosenblatt, F. (1958): The Perceptron: A Probabilistic Model for Information Storage and Organization in the Brain, Cornell Aeronautical Laboratory, Psychological Review, v65, No. 6, pp. 386–408. doi:10.1037/h0042519.

Stewart, M. y Wallis, K. (1984), Introducción a la Econometría, Alianza Editorial.

Tan, Hui Boon & Ashley, Richard, 1999. “Detection And Modeling Of Regression Parameter Variation Across Frequencies,” Macroeconomic Dynamics, Cambridge University Press, vol. 3(01), pages 69-83, March.

Venables, W. N. y Ripley, B. D. (2002), Modern Applied Statistics with S. 4ª Ed., Springer.

Werbos, P. (1990): Backpropagation through time: what it does and how to do it. Proceedings of the IEEE, Volume 78, Issue 10, 1550 - 1560, Oct 1990, doi10.1109/5.58337

White, H. (1980), An Heteroskedastic-Consistent Regression with Independent Observation. Econometrica 48, pp. 817-838.