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Combine MID Objects

Source: R/midlist.R
midlist.Rd

Combines multiple MID models ("mid") or their interpretation results ("midimp", "midcon", "midbrk") into a unified collection object. This is useful for grouping models and their explanations together for seamless comparison, summary, and visualization.

Usage

midlist(...)

as.midlist(x)

Arguments

...

objects to be combined, possibly named. All inputs must inherit from exactly one of the supported base classes: "mid", "midimp", "midcon", or "midbrk". Collection classes (e.g., "mids"-"midrib", "midimps"-"midlist") are also accepted and will be flattened appropriately.

x

object to be coerced or tested.

Value

midlist() returns a list-based collection object inheriting from "midlist" and the appropriate collection class (e.g., "midcons"-"midlist"). If a single "midrib" object is provided, the original object is returned as-is.

as.midlist() returns a "midlist" object with a type-class "mids", "midimps", "midbrks", or "midcons".

Details

The midlist() function acts as a polymorphic constructor for collection objects. Depending on the class of the input objects, it automatically assigns the appropriate classes (e.g., "mid" objects become a "mids"-"midlist" collection; "midimp" objects become a "midimps"-"midlist" collection). All objects provided in ... must belong to the same base class.

If a single "midrib" object is provided, it is returned as-is, preserving its optimized struct-of-arrays format. However, if a "midrib" object is combined with other objects via ..., it is automatically coerced into a pure list (array of structures) to ensure structural consistency before concatenation.

See also

extract.midlist, labels.midlist

Examples

# Fit models using the built-in anscombe dataset
fit1 <- lm(cbind(y1, y2, y3) ~ x1, data = anscombe)
fit2 <- lm(y4 ~ x4, data = anscombe)

# Create interpretation objects
# mid1 is a "midrib" collection containing 3 models
mid1 <- interpret(cbind(y1, y2, y3) ~ x1, data = anscombe, model = fit1)
class(mid1)
#> [1] "mids"   "midrib"
# mid2 is a single "mid" object
mid2 <- interpret(y4 ~ x4, data = anscombe, model = fit2)

# Combine a "midrib" and a "mid" into a single "midlist" collection.
collection <- midlist(mid1, y4 = mid2)

# Check the labels of the combined collection
labels(collection)
#> [1] "y1" "y2" "y3" "y4"

# The resulting object is a flat list of models
class(collection)
#> [1] "mids"    "midlist"