Models fit gene expression trends in pseudotime; they assume some parametric form for the gene trend and estimate parameters using an objective function. Note that some models require you to have R and rpy2 installed.

models.GAM(adata[, n_knots, spline_order, ...])

Fit Generalized Additive Models (GAMs) using pygam.

models.GAMR(adata[, n_knots, distribution, ...])

Wrapper around R's mgcv package for fitting Generalized Additive Models (GAMs).

models.SKLearnModel(adata, model[, ...])

Wrapper around sklearn.base.BaseEstimator.