r4pde 0.2.2

New functions

Added functional_rate(): Estimates instantaneous rates of plant disease progress () and associated uncertainty from epidemic trajectories fitted by functional_curves(). Supports response and link scale derivatives via GAM linear predictor matrix differences, handles boundary conditions without extrapolation, accounts for zero-epidemic curves and negative rates, and computes key rate phenotypes (, , growth duration, cumulative positive growth, and growth windows). Includes S3 methods: print(), summary(), plot(), and augment().

functional_curves(): Fixed smooth term label inspection during prediction so that .unit experimental unit and block random effects are correctly identified and supplied to predict.gam().

Added a suite of tools for Disease Suppression Profiles (DSP) to evaluate fungicide efficacy over time: functional_contrast(), functional_summary(), plot_dsp(), rank_dsp(), plot_dsp_rank_heatmap(), and simulate_dsp_data().

functional_curves(): Updated the GAM formula to fit independent smooths per treatment by default (trt + s(time, by=trt)), avoiding artifactual drops (“caimento”) at the tails of flat curves. Added the global_smooth parameter to allow users to opt-in to the previous Global-Specific smoothing behavior.
simulate_dsp_data(): Adjusted the amplitudes of the simulated suppression profiles (“Early”, “Late”, “Persistent”) to achieve exactly a 70% reduction in AUDPC compared to the unsprayed control, representing a realistic fungicide efficacy scenario.
Updated _pkgdown.yml to include the newly exported functional PCA and DSP functions in the “Functional Analysis” reference index, resolving site build errors.

Introduced a modular functional-analysis workflow based on functional_curves(), functional_distances(), functional_pca(), functional_resistance(), and related methods.

functional_pca(): Performs functional principal component analysis on fitted disease progress curves to decompose variation among epidemic trajectories into orthogonal temporal components. Includes plotting and extractor functions.
functional_curves(): Fits genotype-specific epidemic trajectories using GAM, with support for genotype-level covariates.
functional_distances(): Computes pairwise functional distances among fitted curves and performs hierarchical clustering and permutation testing.
functional_resistance(): Calculates Functional Resistance Index (FRI) and Stability-Adjusted Functional Resistance Index (SAFRI) with support for stratified rankings and bootstrap-supported classification.
suggest_k(): Helper function to recommend GAM smoothing parameters (k_smooth, k_trt, k_env, gamma) based on data structure; supports tidy-eval column names and can infer replication from a data frame.

Added support for genotype-level auxiliary covariates (e.g., heading_group) to adjust functional curves and resistance rankings, allowing for better distinction between genetic resistance and phenological escape.
Improved bootstrap methodology for resistance classification with support for stratified group comparisons.
Updated diagnose_curves(), plot_curves(), and plot_dendrogram() to support the new functional analysis object classes.

Added functional_instability() for computing normalized functional instability (NFI) of genotype-by-environment epidemic curves, with optional decomposition into spatial and temporal components.
Added plot_functional_instability() for visualizing overall, spatial, and temporal NFI results as bar charts.

Added get_era5() for retrieving ERA5 reanalysis weather data via Open-Meteo API.
Added get_brdwgd() for extracting daily weather data from the Brazilian Daily Weather Gridded Data (BR-DWGD) NetCDF files.
Added plotting and diagnostic helpers for curve models.