Feat/zinb simulation and toy model#6
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Implements several enhancements to the simulation framework:
1. Introduces a Zero-Inflated Negative Binomial (ZINB) distribution
as a new option for treatment generation (gps_mod = 5) in
`functions/simulation_functions.R`. This allows for simulating
count-based treatments with excess zeros. Includes parameters
zinb_mu, zinb_theta, and zinb_pi for customization.
2. Adds `toy_model_simulation.R`, a simplified and heavily commented
script. This serves as an accessible entry point for users to
understand the simulation mechanics by running a single,
configurable scenario.
3. Updates `1_run_simulation.R` to include the new ZINB gps_mod
in its iteration loop.
4. Enhances documentation in `README.md` to describe the toy model
and the new ZINB treatment generation mechanism. Code comments
were also added/updated for clarity.
Introduces `nb_model_simulation.R`, a standalone script demonstrating how to simulate Negative Binomial (NB) distributed treatment. This script utilizes the existing ZINB generation mechanism (gps_mod = 5) by setting the zero-inflation probability (zinb_pi) to 0. It is structured similarly to toy_model_simulation.R for clarity and ease of use, serving as a clear example for users wanting to simulate NB treatments.
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