fitgrid
fitgrid is a Python package originally designed to streamline the
computation and interpretation of regression ERPs (rERPs) as described
by Smith and Kutas ([SmiKut2015]). That report articulates the
conceptual foundation of rERPs as time-series of estimated regression
variable coefficients, \(\hat{\beta}_i\), for linear models of the
form \(\beta_0 + \beta_1 X_1 + \ldots + \beta_n X_n + e\) and
their role in modeling EEG and other types of time-series data.
The fitgrid package is intended for researchers with a basic working
knowledge of scientific computing in Python. It provides access to the
multichannel time-series regression modeling computations with one
line of code and the familar ordinary least squares (OLS) and linear
mixed-effects regression (LMER) modeling formulas shared by Python and
R (patsy [Smith2020]; lm [R2020], lme4::lmer
[BatesEtAl2015]). The fit results across time and channels are
available on demand and returned as a tidy indexed
pandas.DataFrame with one line of code and the same syntax
used to access results in a single fit object. These interfaces allow
researchers to conduct this type of modeling flexibly, efficiently,
informatively, and reproducibly with familiar tools and minimal
programming in Python data analysis workflows.
For a summary of the problem fitgrid solves, why it is worth
solving, and how it is solved, see the About fitgrid. The
User Guide has information on specific topics including how the
OLS models are fit in Python statsmodels [SeaSkiPer2010] and the
LMER models are fit in R (lme4::lmer, lmerTest [KuzBroChr2017])
via pymer4 [Jolly2018] and rpy2 [Gautier2021] under the
hood. The Examples Gallery contains executable fitgrid vignettes
with simulated data, experimental EEG recordings, and NOAA tide and
atmospheric observations. The Workflow Outline example illustrates the
fitgrid modeling pipeline. The examples can be downloaded as
Python scripts or Jupyter notebooks thanks to sphinx-gallery. The API is a complete listing of
fitgrid classes, methods, attributes, and functions. The
Bibliography includes References and
Research reports using fitgrid.
