Group-based Trajectory Modelling (GBTM) in Python
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Updated
Aug 5, 2025 - Python
Group-based Trajectory Modelling (GBTM) in Python
An R package for Bayesian estimation of the probability of informed trading.
R, Julia and Python implementation of the two submarket fully endogenized finite mixture model used in forthcoming articles by Fuad and Farmer (202-) and Fuad, Farmer, and Abidemi (202-).
Comparing submarket separation techniques using Atlanta housing data. Models include fully endogenized FMM, hierarchical linear model, and quasi linear model.
A new way to calculate thermal summation constants for forensically useful insects using fuzzy regression
Demo codes for Advanced Natural Resource Economics course by Dr. Farmer and TA-ed by yours truly.
A web app to calculate Bayes Factors (BF) and Approximate Correct Model Probability (cmP) values.
Estimate a univariate mixture of normals distribution using moments and the EM algorithm
Fit a univariate mixture of normals to simulated data using the EM algorithm, in Python
A modular Python framework for fitting finite mixture EM models to longitudinal data. Includes variants with QP decomposition (within–between effects) and covariate-dependent priors (CRE models). Designed for simulation studies and model comparison (AIC/BIC-based selection).
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