Predict the statistics of an underlying reference distribution from a mixture distribution of raw clinical measurements (healthy and pathological patients). Uses pre-trained convolutional neural networks to estimate means, standard deviations, correlations, and reference fractions from 1D or 2D sample data.
Jack
Maintainer: Jack <your.email@example.com>
The main functions in this package are:
predict_rinet(): Automatically detect and predict (recommended)
predict_rinet_1d(): Predict statistics from 1D mixture samples
predict_rinet_2d(): Predict statistics from 2D mixture samples
Models are automatically loaded on first use and cached for efficiency.
Model files should be placed in inst/models/ with names:
rinet_1d.keras - 1D model
rinet_2d.keras - 2D model
scaler_1d.pkl - 1D scaler
scaler_2d.pkl - 2D scaler