Imput missing values by variable samplingd distribution
impute_by_sampling_distribution.RdThis function take advantage of generate_synthetic_object to impute
missing data. Read help(generate_synthetic_object) for more information.
Argumentos
- obj
A dataframe, numeric vector or character/factor vector.
- seed
Specify seed when replication is desired.
Ejemplos
impute_by_sampling_distribution(c(mtcars$mpg,NA,NA,NA,NA,NA))
#> [1] 21.0 21.0 22.8 21.4 18.7 18.1 14.3 24.4 22.8 19.2 17.8 16.4 17.3 15.2 10.4
#> [16] 10.4 14.7 32.4 30.4 33.9 21.5 15.5 15.2 13.3 19.2 27.3 26.0 30.4 15.8 19.7
#> [31] 15.0 21.4 28.9 31.7 20.5 25.5 20.2
data_temp <- data.frame(
x = c(mtcars$mpg,NA,NA,NA,NA,NA),
y = c(mtcars$cyl,NA,NA,NA,NA,NA))
as.data.frame(impute_by_sampling_distribution(data_temp) )
#> Error in impute_by_sampling_distribution(data_temp): objeto 'obj_label' no encontrado
dplyr::mutate(data_temp, x_impute = impute_by_sampling_distribution(x))
#> x y x_impute
#> 1 21.0 6 21.0
#> 2 21.0 6 21.0
#> 3 22.8 4 22.8
#> 4 21.4 6 21.4
#> 5 18.7 8 18.7
#> 6 18.1 6 18.1
#> 7 14.3 8 14.3
#> 8 24.4 4 24.4
#> 9 22.8 4 22.8
#> 10 19.2 6 19.2
#> 11 17.8 6 17.8
#> 12 16.4 8 16.4
#> 13 17.3 8 17.3
#> 14 15.2 8 15.2
#> 15 10.4 8 10.4
#> 16 10.4 8 10.4
#> 17 14.7 8 14.7
#> 18 32.4 4 32.4
#> 19 30.4 4 30.4
#> 20 33.9 4 33.9
#> 21 21.5 4 21.5
#> 22 15.5 8 15.5
#> 23 15.2 8 15.2
#> 24 13.3 8 13.3
#> 25 19.2 8 19.2
#> 26 27.3 4 27.3
#> 27 26.0 4 26.0
#> 28 30.4 4 30.4
#> 29 15.8 8 15.8
#> 30 19.7 6 19.7
#> 31 15.0 8 15.0
#> 32 21.4 4 21.4
#> 33 NA NA 22.7
#> 34 NA NA 15.4
#> 35 NA NA 18.0
#> 36 NA NA 17.7
#> 37 NA NA 23.9