The “aft” function fits models of the form:

Y=log(T)=g0+g1*Z1+g2*Z2+...+sigma*epsilon

where usually T is a time to event variable and g0, g1, ... and sigma are to be estimated. Since T is a time to event variable censoring might be involved. The “aft” function deals with possibly right and/or left censored data. With "sigma" we denote the scale parameter, and the regression coefficients are denoted by vector g=[g0 g1 g2...]. The covariates are denoted with Z1, Z2, ...

The distribution of "epsilon" defines the distribution of T. The user can specify this distribution using one of the following available options:
Exponential, Weibull, Log-normal, Log-logistic, Generalized Gamma.

The “aft” routine is supposed to be a MATLAB alternative to proc lifereg of SAS, or survreg of R. However the “aft” has less options.