Run a Functional Data Analysis Workflow — run_fda

Runs the main FDA workflow for one or more weather variables: creates subject-by-time matrices, computes smoothed group means, compares two groups with interval-wise permutation tests, and stores tidy summaries for plotting and feature extraction.

Usage

run_fda_analysis(
  data,
  id_col,
  time_col,
  group_col,
  value_cols,
  value_labels = NULL,
  alpha = 0.05,
  n_permutations = 1000,
  smooth_method = c("spline", "lowess", "none"),
  smooth_args = list(),
  time_grid = NULL,
  n_time_grid = 300,
  reference_group = NULL,
  comparison_group = NULL,
  quiet = TRUE
)

Arguments

data: A data frame in long format.
id_col: Subject identifier column.
time_col: Time column, such as relative day or days after planting.
group_col: Grouping column with exactly two groups.
value_cols: Weather variable columns to analyze.
value_labels: Optional named character vector or data frame with variable and label columns used for plot labels.
alpha: One or more significance levels used to extract intervals.
n_permutations: Number of permutations used by the interval-wise test.
smooth_method: Smoothing method used for group mean curves. One of "none", "lowess", or "spline".
smooth_args: Named list of extra arguments passed to the smoothing method.
time_grid: Optional grid for plotting smoothed group means. If NULL, a dense grid is created from the observed time range.
n_time_grid: Number of points in the dense plotting grid when time_grid = NULL.
reference_group: Optional reference group. If NULL, the first group level or first observed group is used.
comparison_group: Optional comparison group. If NULL, the other group is used.
quiet: Logical; if TRUE, suppresses routine console output emitted by fdatest::ITP2bspline().

Value

A windcut_fda_analysis object with matrices, summaries, interval-test results, and tidy interval summaries.