3.4.2. statsmodels.emplike.aft_el¶
Accelerated Failure Time (AFT) Model with empirical likelihood inference.
AFT regression analysis is applicable when the researcher has access to a randomly right censored dependent variable, a matrix of exogenous variables and an indicatior variable (delta) that takes a value of 0 if the observation is censored and 1 otherwise.
3.4.2.1. AFT References¶
Stute, W. (1993). “Consistent Estimation Under Random Censorship when Covariables are Present.” Journal of Multivariate Analysis. Vol. 45. Iss. 1. 89-103
3.4.2.2. EL and AFT References¶
Zhou, Kim And Bathke. “Empirical Likelihood Analysis for the Heteroskedastic Accelerated Failure Time Model.” Manuscript: URL: www.ms.uky.edu/~mai/research/CasewiseEL20080724.pdf
Zhou, M. (2005). Empirical Likelihood Ratio with Arbitrarily Censored/ Truncated Data by EM Algorithm. Journal of Computational and Graphical Statistics. 14:3, 643-656.
3.4.2.3. Functions¶
add_constant(data[, prepend, has_constant]) |
This appends a column of ones to an array if prepend==False. |
3.4.2.4. Classes¶
AFTResults(model) |
|
OLS(endog[, exog, missing, hasconst]) |
A simple ordinary least squares model. |
OptAFT() |
Provides optimization functions used in estimating and conducting inference in an AFT model. |
WLS(endog, exog[, weights, missing, hasconst]) |
A regression model with diagonal but non-identity covariance structure. |
emplikeAFT(endog, exog, censors) |
Class for estimating and conducting inference in an AFT model. |
3.4.2.5. Exceptions¶
IterationLimitWarning |