Implements a flexible, versatile, and computationally tractable model for density regression based on a single-weights dependent Dirichlet process mixture of normal distributions model for univariate continuous responses. The model assumes an additive structure for the mean of each mixture component and the effects of continuous covariates are captured through smooth nonlinear functions. The key components of our modelling approach are penalised B-splines and their bivariate tensor product extension. The proposed method can also easily deal with parametric effects of categorical covariates, linear effects of continuous covariates, interactions between categorical and/or continuous covariates, varying coefficient terms, and random effects. Please see Rodriguez-Alvarez, Inacio et al. (2025) for more details.

Provides an implementation of the framework of reversed graph embedding (RGE) which projects data into a reduced dimensional space while constructs a principal tree which passes through the middle of the data simultaneously. DDRTree shows superiority to alternatives (Wishbone, DPT) for inferring the ordering as well as the intrinsic structure of the single cell genomics data. In general, it could be used to reconstruct the temporal progression as well as bifurcation structure of any datatype.

A sparse Partial Least Squares implementation which uses soft-threshold
	estimation of the covariance matrices and therein introduces
	sparsity. Number of components and regularization coefficients are automatically set.

Smooth testing of goodness of fit. These tests are data
    driven (alternative hypothesis is dynamically selected based on data). In this
    package you will find various tests for exponent, Gaussian, Gumbel and uniform
    distribution.

Implements a Bayesian algorithm for overcoming weak separation in Bayesian latent class analysis. 
    Reference: Li et al. (2023) <arXiv:2306.04700>.

Statistical deadband algorithms are based on the Send-On-Delta concept as in Miskowicz(2006,<doi:10.3390/s6010049>). A collection of functions compare effectiveness and fidelity of sampled signals using statistical deadband algorithms.