R: Dynamic Programming Based Gaussian Mixture Modelling Tool for 1D and 2D Data

# Dynamic Programming Based Gaussian Mixture Modelling Tool for 1D and 2D Data

## Documentation for package ‘dpGMM’ version 1.0.0

- DESCRIPTION file
- Package README

## Help Pages

binned | Data example of binned problem in mass spectrometry
EM_iter | Expectation-maximization algorithm for 1D data
EM_iter_2D | Expectation-maximization algorithm for 2D data
example | Data of 1D mixed-normal distributions
example2D | Data of 2D mixed-normal distributions
find_class_2D | Class assignment for 2D Gaussian Mixture Model data
find_thr_by_dist | Thresholds estimations for 1D from GMM distribution
find_thr_by_params | Thresholds estimations for 1D from GMM parameters
gaussian_mixture_2D | Gaussian mixture decomposition for 2D data
gaussian_mixture_vector | Gaussian mixture decomposition for 1D data
generate_dist | Generation of GMM data with high precision
generate_dset2D | Generator of multiple random 2D mixed-normal distributions
generate_norm1D | Generator of 1D mixed-normal distributions
generate_norm2D | Generator of 2D mixed-normal distributions
GMM_1D_opts | Default configuration for 1D Gaussian Mixture decomposition
GMM_2D_opts | Default configuration for 2D Gaussian Mixture decomposition
img_to_coords | 2D plot support
plot_gmm_1D | Plot of GMM decomposition for 1D data
plot_gmm_2D_binned | Plot of GMM decomposition for 2D binned data
plot_gmm_2D_orig | Plot of GMM decomposition for 2D data
plot_QQplot | QQplot of GMM decomposition for 1D data
runGMM | Function to fit Gaussian Mixture Model (GMM) to 1D data
runGMM2D | Function to fit Gaussian Mixture Model (GMM) to 2D data