  CurvPy is an open-source Python library for automated curve fitting and
regression analysis, aiming to make advanced statistical and machine learning
techniques more accessible. This paper explores the mathematical foundations
and implementation of key CurvPy components for optimization, smoothing,
imputation, summarization, visualization, regression, evaluation, and tuning.
The methodology leverages well-established statistical and computational
algorithms adapted through both simplification and exposure of advanced options
to balance usability and customizability. Mathematical techniques utilized
include least squares estimation, Savitzky-Golay filtering, matrix completion,
gradient descent optimization, regularization, basis function regression, and
standard model evaluation metrics.
