gen_surv 0.6.3

A Python package for simulating survival data, inspired by the R package genSurv

gen_surv

gen_surv is a Python package for simulating survival data under a variety of models, inspired by the R package genSurv. It supports data generation for:

• Cox Proportional Hazards Models (CPHM)
• Continuous-Time Markov Models (CMM)
• Time-Dependent Covariate Models (TDCM)
• Time-Homogeneous Hidden Markov Models (THMM)

---

📦 Installation

poetry install

✨ Features

• Consistent interface across models
• Censoring support (uniform or exponential)
• Easy integration with pandas and NumPy
• Suitable for benchmarking survival algorithms and teaching

🧪 Example

from gen_surv.cphm import gen_cphm

df = gen_cphm(
    n=100,
    model_cens="uniform",
    cens_par=1.0,
    beta=0.5,
    covar=2.0
)
print(df.head())

from gen_surv import generate

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

print(df.head())

🔧 Available Generators

Function	Description
gen_cphm()	Cox Proportional Hazards Model
gen_cmm()	Continuous-Time Multi-State Markov Model
gen_tdcm()	Time-Dependent Covariate Model
gen_thmm()	Time-Homogeneous Markov Model

genSurvPy/
├── gen_surv/             # Pacote principal
│   ├── __main__.py       # Interface CLI via python -m
│   ├── cphm.py
│   ├── cmm.py
│   ├── tdcm.py
│   ├── thmm.py
│   ├── censoring.py
│   ├── bivariate.py
│   ├── validate.py
│
├── tests/                # Testes automatizados
│   ├── test_cphm.py
│   ├── test_cmm.py
│   ├── test_tdcm.py
│   ├── test_thmm.py
│
├── examples/             # Exemplos de uso
│   ├── run_cphm.py
│   ├── ...
│
├── pyproject.toml        # Configurado com Poetry
├── README.md
├── LICENSE
├── .gitignore

🧠 License

MIT License. See LICENSE for details.