HADES 1.1 (released March 09, 2009) is written in Matlab and can be downloaded from HADES. This program implements nonparametric hazard and density estimation from aggregated (binned) or censored data. Input formats include lifetables. The algorithm for hazard function estimation combines smoothing with local linear least squares with a transformation approach to reduce discretization bias. Options include centralized mortality rates q_c (method =1) or the transformation psi(x) = log(4/(2-x*Delta)-1) (method = 2, default). Density estimation is implemented via histogram smoothing by local linear least squares or via hazard rate estimation for the censored case. A related program for continuously observed non-aggregated survival data is the R routine muhaz . The development of HADES has been supported by various NSF grants. Contributors to the code include Hans-Georg Muller (initial version), Kun Chen (updated version), Shuang Wu (curent version).

References:

Müller, H.G., Wang, J.L. (1994). Hazard rate estimation under random censoring with varying kernels and bandwidths. Biometrics 50, 61-76.

Müller, H.G., Wang, J.L., Capra, W.B. (1997). From lifetables to hazard rates: The transformation approach. Biometrika 84, 881-892.

Wang, J.L., Müller, H.G., Capra, W.B. (1998). Analysis of oldest-old mortality: Lifetables revisited. Annals of Statistics 26, 126-163.