Description Usage Arguments Details Value See Also Examples
View source: R/measure_correlation.R
Measures a relationship between two supplied completed data sets, typically generated by two sequential iterations of the missForest procedure. Given by the rank correlation or proportion of stationary values for ordered (including continuous) and categorical data respectively.
1 | measure_correlation(X, Y, X_init, indicator, method = "spearman")
|
X |
named list; imputed values, in order of appearance by row in original data, of each variable (named) from one iteration within missForest procedure. |
Y |
named list;
imputed values, in order of appearance by row in origina data,
of each variable (named) from the iteration within the missForest
procedure succeeding that used to determine |
X_init |
data.frame; a data set including any of numeric, logical, integer, factor and ordered data types, to be used as the initial state of the missForest procedure. |
indicator |
named list;
an indicator of the missing ( |
method |
character;
passed to |
Measures a relationship between two supplied completed data sets, typically generated by two sequential iterations of the missForest procedure. Intended to be used with the stop criterion that as soon as all values (see below) remain constant or decrease at once, then the missForest procedure is deemed to have converged.
The two values are the;
mean rank correlation of the ordered (including continuous) data between the supplied completed data sets, and;
proportion of stationary categorical data between the two supplied
completed data sets (see stationary_rate
).
The type of correlation can be modified to that of kendall
or
pearson
(not recommended for ordered data) by the method
argument passed on to cor
.
named numeric; two named values:
continuous
mean (rank) correlation of the continuous and ordered data between the two completed data sets, and;
categorical
proportion of stationary values of
categorical (unordered) data between the two completed
data sets (see stationary_rate
).
1 2 3 4 5 | ## Not run:
# simply pass to smirf
smirf(iris, stop.measure=measure_correlation)
## End(Not run)
|
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