General books on statistical computing and computational statistics

Gentle, J.E. (2002) Elements of Computational Statistics, New York: Springer. Broad overview of computationally intensive methods in modern statistics.

Gentle, J.E., Härdle, W. and Mori, Y. (Eds.) (2004) Handbook of Computational Statistics: Concepts and Methods, New York: Springer. Newly edited volume on the history of the emerging field of computational statistics, statistical computing, computational methodology and applications.

Kennedy, W.J. and Gentle, J.E. (1980) Statistical Computing, New York: Marcel Dekker. A pioneering text that describes methods and algorithms for generating random variates, computing distribution functions and quantiles, linear and nonlinear regression, analysis of variance and multivariate analysis. Dated but still useful.

Thisted, R.A. (1988) Elements of Statistical Computing: Numerical Computation, London: Chapman and Hall/CRC Press. A nice text with an emphasis on matrix methods for statisticians, numerical integration, smoothing, etc.

Texts on numerical methods and algorithms

Golub, G. and van Loan, C. (1996) Matrix Computations, Third edition, London: The Johns Hopkins University Press. Indispensable for anyone intending to program their own matrix routines.

Press, W.H., Flannery, B.P., Teukolsky, S.A., and Vetterling, W.T. (1992) Numerical Recipes in Fortran 77: The Art of Scientific Computing, Second edition, Cambridge: Cambridge University Press. A classic.

Press, W.H., Flannery, B.P., Teukolsky, S.A., and Vetterling, W.T. (1996) Numerical Recipes in Fortran 90: The Art of Parallel Scientific Computing. Cambridge: Cambridge University Press. For those interested in parallel processing.

General reference on the Fortran 95 language

Metcalf, M. and Reid, J. (1999) Fortran 90/95 Explained, Second edition, Oxford: Oxford University Press.