Journal Articles:

• 2025:

1. Mestry, D. V., Bhowmick, A. R.*, Demystifying Monte Carlo Methods in R: A Guide from Metropolis-Hastings to Hamiltonian Monte Carlo with Biological Growth Equation Examples (Ecological Modelling, Review Article).

• 2024:

1. Mestry, D. V., Karim A. M. U., Mukherjee J., Bhowmick A. R.*, Identifying key drivers of extinction for Chitala populations: data-driven insights from an intraguild predation model using a Bayesian framework (Environmental and Ecological Statistics).

• 2021:

1. Mestry, D. V., Bhowmick, A. R.*, On estimating the parameters of generalized logistic model from census data: Drawback of classical approach and reliable inference using Bayesian framework, https://doi.org/10.1016/j.ecoinf.2021.101249, (Ecological Informatics, Elsevier, vol. 62). 

Submitted Articles:

1. Mestry, D. V., Singh, P., Rocklöv, J., Bhowmick, A. R., Deciphering Memory Patterns in Eco-Epidemiological systems through the lens of BaFOMS: A Bayesian Fractional Order Model Selection Method (Mathematics and Computers in Simulation, Status: Under Review).

2. Mestry, D. V., Bhowmick, A. R., Getting Started with MCMC Simulation: A Practical Tutorial Using R and Applications to Real Data (Ecological Modelling, Status: Under Review). 

3. Rawat, M., Mestry, D. V., Bhowmick, A. R., Adaptive Bayesian Walk: A Likelihood-Free Framework for Model Selection and Parameter Inference via ABC (Statistics and Computing, Status: Under Review).

4. Chaugule S., Mestry, D. V., Bhowmick, A. R., Approximate Bayesian Computation: A Review with Growth Curve Models and Real-World Applications in Julia. (AStA Advances in Statistical Analysis, Status: With Editor).

Online published documents:

1. Introduction to Bayesian Computing (https://dipalimestry96.github.io/Introduction-to-Bayesian-Computing/), published on GitHub on September 23, 2024.