interpolate_group_complete: Given a grouped dataframe and a line, interpolate numeric...
In EpidemiumOpenCancer/OpenCancer: Build statistical models to understand cancer causes
Description
Usage
Arguments
Details
Value
Examples
Description
Given a grouped dataframe and a line, interpolate numeric variables and impute missing data from non numeric variables with an extended locf preserving the dimension
Usage
1
interpolate_group_complete(missingdata, df, i = 1, year.var = "year")
Arguments
missingdata
A dataframe listing groups and variables
that must be changed
i
Line index of missingdata that will be looked
Details
Intermediate function, do not use
Value
A list with several components: lines and cols
return the lines and columns concerned by imputation, after
returns the relevant lines and columns imputed while change
stores as a dummy whether data have been imputed with interpolation or extended locf.
Examples
1
# See \code{interpolate_data_complete} source code
EpidemiumOpenCancer/OpenCancer documentation built on May 12, 2019, 7:46 a.m.
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Description Usage Arguments Details Value Examples
Description
Given a grouped dataframe and a line, interpolate numeric variables and impute missing data from non numeric variables with an extended locf preserving the dimension
Usage
1 | interpolate_group_complete(missingdata, df, i = 1, year.var = "year")
|
Arguments
missingdata |
A dataframe listing groups and variables that must be changed |
i |
Line index of missingdata that will be looked |
Details
Intermediate function, do not use
Value
A list with several components: lines and cols
return the lines and columns concerned by imputation, after
returns the relevant lines and columns imputed while change
stores as a dummy whether data have been imputed with interpolation or extended locf.
Examples
1 | # See \code{interpolate_data_complete} source code
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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