Exploratory integration of available numeric domain observations. A larger score is not automatically greater resilience: justify feature orientation, the reference function and the observation window.
Usage
rri_pipeline(
dat = NULL,
soil = NULL,
plant = NULL,
micro = NULL,
id = NULL,
domain_weights = c(Physio = 0.4, Soil = 0.35, Micro = 0.25),
...
)Arguments
- dat
Optional wide data frame with canonical observation names.
- soil, plant, micro
Optional numeric data frames with aligned rows. Supply these instead of dat to use custom measurement names or partial panels.
- id
Optional identifier data frame in the same row order.
- domain_weights
Named nonnegative weights for Physio, Soil and Micro. Available positive weights are renormalized per row; absent domains stay NA.
- ...
Arguments to rri_pipeline_st, excluding its domain inputs, identifiers and w1/w2/w3 (use domain_weights instead).
Value
An RRI object with row_scores, a scores alias, effective_weights, per-row domain_coverage and n_domains, and a call_mode field.
Details
Known hidden simulator columns are excluded. This is a safeguard, not an automatic detector of every possible source of target leakage. Cohort-fitted PCA and scaling must not be interpreted as a trained predictor. Use rri_reference_scores for fixed, independently justified reference anchors. A reduced panel changes the estimand; compare panels through sensitivity analysis rather than treating their scores as interchangeable.
Examples
x <- data.frame(Eh = c(50, 100, 150, 200), pH = c(5, 5.5, 6, 6.5))
z <- rri_pipeline(soil = x, method_soil = "scale",
direction_anchor_soil = "Eh")
#> Warning: Unanchored latent axes have arbitrary signs; RRI is exploratory, not directionally validated resilience.
z$row_scores
#> Physio Soil Micro RRI domain_coverage n_domains Micro_abundance
#> 1 NA 0.0000000 NA 0.0000000 0.35 1 NA
#> 2 NA 0.3333333 NA 0.3333333 0.35 1 NA
#> 3 NA 0.6666667 NA 0.6666667 0.35 1 NA
#> 4 NA 1.0000000 NA 1.0000000 0.35 1 NA
#> Micro_network Micro_mfa
#> 1 NA NA
#> 2 NA NA
#> 3 NA NA
#> 4 NA NA