gen_surv

gen_surv is a Python package for simulating survival data under various models, inspired by the R package genSurv.

It includes generators for:

  • Cox Proportional Hazards Models (CPHM)

  • Continuous-Time Markov Models (CMM)

  • Time-Dependent Covariate Models (TDCM)

  • Time-Homogeneous Hidden Markov Models (THMM)

  • Accelerated Failure Time (AFT) Log-Normal Models

Key functions include generate(), gen_cphm(), gen_cmm(), gen_tdcm(), gen_thmm(), gen_aft_log_normal(), sample_bivariate_distribution(), runifcens(), and rexpocens().

See the Getting Started guide for installation instructions.

📚 Modules

Contents

🚀 Usage Example

from gen_surv import generate

# CPHM
generate(model="cphm", n=100, model_cens="uniform", cens_par=1.0, beta=0.5, covar=2.0)

# AFT Log-Normal
generate(model="aft_ln", n=100, beta=[0.5, -0.3], sigma=1.0, model_cens="exponential", cens_par=3.0)

# CMM
generate(model="cmm", n=100, model_cens="exponential", cens_par=2.0,
         qmat=[[0, 0.1], [0.05, 0]], p0=[1.0, 0.0])

# TDCM
generate(model="tdcm", n=100, dist="weibull", corr=0.5,
         dist_par=[1, 2, 1, 2], model_cens="uniform", cens_par=1.0,
         beta=[0.1, 0.2, 0.3], lam=1.0)

# THMM
generate(model="thmm", n=100, qmat=[[0, 0.2, 0], [0.1, 0, 0.1], [0, 0.3, 0]],
         emission_pars={"mu": [0.0, 1.0, 2.0], "sigma": [0.5, 0.5, 0.5]},
         p0=[1.0, 0.0, 0.0], model_cens="exponential", cens_par=3.0)

⌨️ Command-Line Usage

Generate datasets directly from the terminal:

python -m gen_surv dataset aft_ln --n 100 > data.csv

Repository Layout

genSurvPy/
├── gen_surv/
│   └── ...
├── tests/
├── examples/
├── docs/
├── scripts/
├── tasks.py
└── TODO.md

Citation

If you use gen_surv in your work, please cite it using the metadata in CITATION.cff.

Author

Diogo Ribeiro — ESMAD - Instituto Politécnico do Porto