| domir | R Documentation |
Parses input object to obtain list of names, determines all required combinations of subsets of the name list, submits name list subsets to a function as the input type, and computes dominance decomposition statistics based on the returned values from the function.
domir(.obj, ...)
## S3 method for class 'formula'
domir(
.obj,
.fct,
.set = NULL,
.wst = NULL,
.all = NULL,
.adj = FALSE,
.cdl = TRUE,
.cpt = TRUE,
.rev = FALSE,
.cst = NULL,
.prg = FALSE,
...
)
## S3 method for class 'formula_list'
domir(
.obj,
.fct,
.set = NULL,
.wst = NULL,
.all = NULL,
.adj = FALSE,
.cdl = TRUE,
.cpt = TRUE,
.rev = FALSE,
.cst = NULL,
.prg = FALSE,
...
)
.obj |
A Parsed to produce list of names. Combinations of subsets the name list are
The name list subsets submitted to |
... |
Passes arguments to other methods during method dispatch;
passes arguments to the function in |
.fct |
A Applied to all subsets of elements as received from |
.set |
A Must be comprised of elements of the same class as |
.wst |
Not yet used. |
.all |
A Must be the same class as |
.adj |
Logical. If |
.cdl |
Logical. If |
.cpt |
Logical. If |
.rev |
Logical. If |
.cst |
Object of class c("SOCKcluster", "cluster") from
When non- |
.prg |
Logical. If |
.objs is parsed into a name list that is used to determine
the required number of combinations of subsets of the name list
included the dominance analysis. How the name list is obtained
depends on .obj's class.
formulaThe formula creates a name list using all terms in the formula.
The terms are obtained using terms.formula. All processing
that is normally applied to the right hand side of a formula is
implemented (see formula).
A response/left hand side is not required but, if present, is
included in all formulas passed to .fct.
formula_listThe formula_list creates a name list out of response-term pairs.
The terms are obtained using terms.formula applied to each individual
formula in the list.
By default, names obtained from .obj are all considered separate
'value-generating names' with the same priority.
Each value-generating name will be a separate element when
computing combination subsets and will be compared to all other
value-generating names.
formulas and formula_list elements are assumed to have an intercept
except if explicitly removed with a - 1 in the formula(s) in .obj.
If removed, the intercept will be removed in all formula(s) in each
sapply-ed subset to .fct.
If offsets are included, they are passed, like intercepts, while
sapply-ing subsets to .fct.
All methods' default behavior that considers all value-generating names
to be of equal priority can be overriden using .set and .all arguments.
Names in .set and .all must also be present in .obj.
.set.set binds together value-generating names such that
they are of equal priority and are never separated when submitted to
.fct.
Thus, the elements in .set bound together contribute jointly to the
returned value and are considered, effectively, a single
value-generating name.
If list elements in .set are named, this name will be used in all
returned results as the name of the set of value-generating names bound
together.
.set thus considers the value-generating names an 'inseparable set' in the
dominance analysis and are always included or excluded together.
.all.all gives immediate priority to value-generating names.
The value-generating names in .all are bound together, are
ascribed their full amount of the returned value from .fct, and
are not adjusted for contribution of other value-generating names.
The value of .fct ascribed to the value-generating names bound
together in .all is returned separately from, and not directly
compared to, the other value-generating names.
The formula method for .all does not allowthe submitted formula to have
a left hand side.
.all includes the value-generating names in 'all subsets' submitted to
the dominance analysis which effectively removes the value associated with
this set of names.
.adj.adj indicates that an intercept-only model should be supplied to .fct.
This intercept-only subset is given most immediate priority and the
value of .fct ascribed to it is removed from all other
value-generating names and sets including those in .all.
The formula method will submit an intercept-only formula to .fct.
The formula_list method creates a separate, intercept-only subset for each
of the formulas in the list.
Both the formula and formula_list methods will respect the user's
removal of an intercept and or inclusion of an offset.
.adj then 'adjusts' the returned value for a non-0 value-returning
null model when no value generating names are included. This is often
useful when a predictive model's fit metric is not 0 when no
predictive factors are included in the model.
All methods submit combinations of names as an object of the same class as
.obj. A formula in .obj will submit all combinations of names as
formulas to .fct. A formula_list in .obj will submit all
combinations of subsets of names as formula_lists to .fct.
In the case that .fct requires a different class (e.g.,
a character vector of names, a Formula::Formula see fmllst2Fml) the
subsets of names will have to be processed in .fct to obtain the correct
class.
The all subsets of names will be submitted to .fct as the first, unnamed
argument.
.fct as Analysis Pipeline.fct is expected to be a complete analysis pipeline that receives a
subset of names of the same class as .obj and uses these names in the
class as submitted to generate a returned value of the appropriate
type to dominance analyze. Typically, the returned value is a
scalar fit statistic/metric extracted from a predictive model.
At current, only atomic (i.e., non-list), numeric scalars (i.e.,
vectors of length 1) are allowed as returned values.
The .fct argument is strict about names submitted and returned value
requirements for functions used. A series of checks to ensure the submitted
names and returned value adhere to these requirements.
The checks include whether the .obj can be submitted to .fct without
producing an error and whether the returned value from .fct is a length 1,
atomic, numeric vector.
In most circumstances, the user will have to make their own named or
anonymous function to supply as .fct to satisfy the checks.
Returns an object of class "domir" composed of:
General_DominanceVector of general dominance values.
StandardizedVector of general dominance values normalized to sum to 1.
RanksVector of ranks applied to the general dominance values.
Conditional_DominanceMatrix of conditional dominance values.
Each row represents an element in .obj;
each column represents a number of elements from .obj in a subset.
Complete_DominanceMatrix of proportions of subsets where the name in the row has a larger value than the name in the column. The se proportions determine complete dominance when a value of 1 or 0.
ValueValue returned by .fct with all elements (i.e.,
from .obj, .all, and .adj.
Value_AllValue of .fct associated with elements included
in .all;
when elements are in .adj, will be adjusted for Value_Adjust.
Value_AdjustValue of .fct associated with elements in .adj.
CallThe matched call.
formula methodPrior to version 1.1.0, the formula method allowed a formula
to be submitted to .adj.
Submitting an intercept-only formula as opposed to a
logical has been depreciated and submitting a formula with more than an
intercept is defunct.
The formula and formula_list methods can be used to pass responses,
intercepts, and offsets to all combinations of names.
If the user seeks to include other model components integral to
estimation
(i.e., a random effect term in lme4::glmer()) include them as
update to the submitted formula or formula_list
imbedded in .fct.
Second-order or higher terms (i.e., interactions like ~ a*b) are parsed
by default but not used differently from first-order terms for producing
subsets. The values ascribed to such terms may not be valid unless
the user ensures that second-order and
higher terms are used appropriately in .fct.
## Linear model returning r-square
lm_r2 <-
function(fml, data) {
lm_res <- lm(fml, data = data)
summary(lm_res)[["r.squared"]]
}
domir(mpg ~ am + vs + cyl, lm_r2, data = mtcars)
## Linear model including set
domir(
mpg ~ am + vs + cyl + carb + gear + disp + wt,
lm_r2,
.set = list(~ carb + gear, ~ disp + wt),
data = mtcars
)
## Multivariate regression with multivariate r-square and
## all subsets variable
mlm_rxy <-
function(fml, data, dvnames) {
mlm_res <- lm(fml, data = data)
mlm_pred <- predict(mlm_res)
cancor(mlm_pred, data[dvnames])$cor[[1]]^2
}
domir(
cbind(wt, mpg) ~ vs + cyl + am + carb,
mlm_rxy,
.all = ~ carb,
data = mtcars,
dvnames = c("wt", "mpg")
)
## Named sets
domir(
mpg ~ am + gear + cyl + vs + qsec + drat,
lm_r2,
data = mtcars,
.set =
list(
trns = ~ am + gear,
eng = ~ cyl + vs,
misc = ~ qsec + drat
)
)
## Linear model returning AIC
lm_aic <-
function(fml, data) {
lm_res <- lm(fml, data = data)
AIC(lm_res)
}
domir(
mpg ~ am + carb + cyl,
lm_aic,
.adj = TRUE,
.rev = TRUE,
data = mtcars
)
## 'systemfit' with 'formula_list' method returning AIC
if (requireNamespace("systemfit", quietly = TRUE)) {
domir(
formula_list(mpg ~ am + cyl + carb, qsec ~ wt + cyl + carb),
function(fml) {
res <- systemfit::systemfit(fml, data = mtcars)
AIC(res)
},
.adj = TRUE, .rev = TRUE
)
}
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