Bibliografía completa

Azarang, M. R. y García Dunna, E. (1996). Simulación y análisis de modelos estocásticos. McGraw-Hill.

Demirhan, H. y Bitirim, N. (2016). CryptRndTest: an R package for testing the cryptographic randomness. The R Journal, 8(1), 233-247.

Downham, D.Y. (1970). Algorithm AS 29: The runs up and down test. Journal of the Royal Statistical Society. Series C (Applied Statistics), 19(2), 190-192.

Gilks, W.R. y Wild, P. (1992). Adaptive rejection sampling for Gibbs sampling. Journal of the Royal Statistical Society. Series C (Applied Statistics), 41(2), 337-348.

Hall, S.W. (1994). Analysis of defectivity of semiconductor wafers by contingency table, Proceedings of the Institute of Environmental Sciences, 1, 177-183.

Hyndman, R.J. y Athanasopoulos, G. (2018). Forecasting: principles and practice. OTexts. Disponible online: 2nd edition (forecast), third edition (fable).

Hofert, M. (2018). Elements of Copula Modeling with R, Springer.

Kinderman, A.J. y Monahan, J.F. (1977). Computer generation of random variables using the ratio of uniform deviates. ACM Transactions on Mathematical Software (TOMS), 3(3), 257-260.

Knuth, D.E. (1969). The Art of Computer Programming. Volume 2. Addison-Wesley.

Knuth, D.E. (2002). The Art of Computer Programming. Volume 2, third edition, ninth printing. Addison-Wesley.

L’Ecuyer, P. (1999). Good parameters and implementations for combined multiple recursive random number generators. Operations Research, 47, 159–164.

L’Ecuyer, P. y Simard, R. (2007). TestU01: A C library for empirical testing of random number generators. ACM Transactions on Mathematical Software (TOMS), 33(4), 1-40.

Law, A.M. y Kelton, W.D. (1991). Simulation, modeling and analysis. McGraw-Hill.

Liu, J.S. (2004). Monte Carlo strategies in scientific computing. Springer.

Marsaglia, G. y Tsang, W.W. (2002). Some difficult-to-pass tests of randomness. Journal of Statistical Software, 7(3), 1-9.

Marsaglia, G., Zaman, A. y Tsang, W.W. (1990). Toward a universal random number generator. Stat. Prob. Lett., 9(1), 35-39.

Matsumoto, M. y Nishimura, T. (1998). Mersenne Twister: A 623-dimensionally equidistributed uniform pseudo-random number generator, ACM Transactions on Modeling and Computer Simulation, 8, 3–30.

Nelsen, R.B. (2006). An introduction to copulas, second edition, Springer.

Nelson, R. (1995). Probability, stochastic processes, and queueing theory: the mathematics of computer performance modelling. Springer-Verlag.

Odeh, R.E. y Evans, J.O. (1974). The percentage points of the normal distribution. Journal of the Royal Statistical Society. Series C (Applied Statistics), 23(1), 96-97.

Patefield, W.M. (1981). Algorithm AS 159: An efficient method of generating random r x c tables with given row and column totals. Applied Statistics, 30, 91–97.

Park, S.K. y Miller , K.W. (1988). Random number generators: good ones are hard to find. Communications of the ACM, 31(10), 1192-1201.

Park, S.K., Miller, K.W. y Stockmeyer, P.K. (1993). Technical correspondence. Communications of the ACM, 36(7), 108-110.

Wichura, M.J. (1988) Algorithm AS 241: The Percentage Points of the Normal Distribution. Applied Statistics, 37, 477–484.