Description Usage Arguments Details Value See Also Examples
Test whether intervals contain specified values. These values
are referred to as 'truth' because intervalContainsTruth
is typically used as part of a simulation study,
where the analyst generates the true values, and then
sees whether the model is able to recover these values.
1 2 3 4 5 6 7 | intervalContainsTruth(interval, truth)
## S4 method for signature 'DemographicArray,DemographicArray'
intervalContainsTruth(interval, truth)
## S4 method for signature 'DemographicArray,numeric'
intervalContainsTruth(interval, truth)
|
interval |
A |
truth |
A |
interval
must have the same dimensions
and dimscales as truth
, and also a dimension
with length 2 and dimtype
"quantile"
specifying the intervals.
An interval (l, u)
is said to contain a value v
if l <= t <= u
. The use of <=
, rather than
<
, makes no difference
when l
and u
are real numbers, but does make
a difference when l
and u
are integers.
truth
can be a single number, in which case all dimensions
of interval
, other than the quantile dimension, should
have length 1.
intervalContainsTruth
is stricter about the compatibility
of its arguments than most functions in dembase
.
Although it reorders dimensions and categories
in interval
and truth
, it does not collapse
or expand dimensions, or drop any levels.
When truth
is a DemographicArray
intervalContainsTruth
returns a Values
object with 1
s and 0
s,
rather than an ordinary array of
TRUE
s and FALSE
s. The advantage of the
Values
object is that it can
more easily be collapsed or otherwise manipulated:
see below for an example.
An Values
object, consisting
of 1
s and 0
s, with the same dimensions
as truth
, or, if truth
is a number,
a single 1
or 0
.
Function credibleInterval
creates
interval
objects of the right form
for intervalContainsTruth
. Function MSE
,
is another function that may be useful in simulation studies.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | interval <- Values(array(c(-0.1, 0.2, 0.4, 0.7),
dim = c(2, 2),
dimnames = list(quantile = c("2.5%", "97.5%"),
sex = c("Female", "Male"))))
truth <- ValuesOne(c(0.3, 0.5),
labels = c("Female", "Male"),
name = "sex")
interval
truth
intervalContainsTruth(interval = interval,
truth = truth)
interval <- ValuesOne(c(5L, 8L),
labels = c("5%", "95%"),
name = "quantile")
truth <- 5L
intervalContainsTruth(interval = interval,
truth = truth)
|
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