Removes missing values (rows and column alternatively) to obtain a large full matrix
Conan( X = X, nbstep = Inf, std = FALSE, verbose = FALSE, coercing = NULL, Xout = TRUE )
Arguments
| X | the dataset (matrix) with missing values |
|---|---|
| nbstep | number of cutting steps (may remove several rows or columns at each step) |
| std | (boolean) remove constant covariates |
| verbose | (boolean) to print the result |
| coercing | vector of the covariates to keep (names or index) |
| Xout | (boolean) to export or not the reduced matrix (if not, indices are sufficient) |
Value
Index of remaining individuals
Index of remaining variables
If Xout=TRUE, the reduced dataset without missing values
Examples
#> mpg cyl disp hp drat wt qsec vs am gear carb #> Mazda RX4 21.0 6 160.0 110 3.90 2.620 16.46 0 1 4 4 #> Mazda RX4 Wag 21.0 6 160.0 110 3.90 2.875 17.02 0 1 4 4 #> Datsun 710 22.8 4 108.0 93 3.85 2.320 18.61 NA 1 4 1 #> Hornet 4 Drive 21.4 6 258.0 110 NA 3.215 NA 1 0 3 1 #> Hornet Sportabout 18.7 8 360.0 175 3.15 3.440 17.02 0 0 3 2 #> Valiant 18.1 6 225.0 105 2.76 3.460 20.22 NA 0 3 1 #> Duster 360 14.3 8 360.0 NA 3.21 3.570 15.84 0 0 3 4 #> Merc 240D 24.4 4 146.7 62 3.69 NA 20.00 1 0 4 2 #> Merc 230 22.8 4 140.8 95 3.92 3.150 22.90 1 0 4 2 #> Merc 280 NA 6 167.6 123 3.92 3.440 18.30 1 0 4 4 #> Merc 280C 17.8 6 167.6 123 3.92 3.440 18.90 1 0 4 4 #> Merc 450SE 16.4 8 275.8 180 3.07 4.070 17.40 0 0 3 3 #> Merc 450SL 17.3 8 275.8 180 3.07 3.730 17.60 0 0 3 3 #> Merc 450SLC 15.2 8 275.8 180 NA 3.780 18.00 0 0 3 3 #> Cadillac Fleetwood 10.4 8 472.0 205 2.93 5.250 17.98 0 0 NA 4 #> Lincoln Continental 10.4 8 460.0 215 3.00 NA 17.82 0 0 3 4 #> Chrysler Imperial 14.7 8 440.0 230 3.23 5.345 17.42 0 NA 3 4 #> Fiat 128 NA 4 78.7 66 4.08 2.200 19.47 1 1 4 1 #> Honda Civic 30.4 4 75.7 52 4.93 1.615 18.52 1 NA 4 2 #> Toyota Corolla 33.9 4 71.1 65 4.22 1.835 19.90 1 1 4 1 #> Toyota Corona 21.5 4 120.1 97 3.70 2.465 20.01 1 0 3 1 #> Dodge Challenger 15.5 8 318.0 150 2.76 3.520 16.87 0 0 3 2 #> AMC Javelin 15.2 8 304.0 150 3.15 3.435 17.30 0 0 3 2 #> Camaro Z28 13.3 8 350.0 245 3.73 3.840 15.41 NA 0 3 4 #> Pontiac Firebird 19.2 8 400.0 175 3.08 3.845 17.05 0 0 3 2 #> Fiat X1-9 27.3 4 79.0 66 4.08 1.935 18.90 1 1 4 1 #> Porsche 914-2 26.0 4 120.3 91 4.43 2.140 16.70 0 1 5 2 #> Lotus Europa 30.4 4 95.1 113 3.77 1.513 16.90 1 1 5 2 #> Ford Pantera L 15.8 8 351.0 264 4.22 3.170 14.50 0 1 5 4 #> Ferrari Dino 19.7 6 145.0 175 3.62 2.770 15.50 0 1 5 NA #> Maserati Bora 15.0 NA NA 335 3.54 3.570 14.60 0 1 5 8 #> Volvo 142E 21.4 4 121.0 109 4.11 2.780 18.60 1 1 4 2reduced = Conan(X = datamiss) reduced#> $X #> mpg cyl disp hp drat wt qsec am gear carb #> Mazda RX4 21.0 6 160.0 110 3.90 2.620 16.46 1 4 4 #> Mazda RX4 Wag 21.0 6 160.0 110 3.90 2.875 17.02 1 4 4 #> Datsun 710 22.8 4 108.0 93 3.85 2.320 18.61 1 4 1 #> Hornet Sportabout 18.7 8 360.0 175 3.15 3.440 17.02 0 3 2 #> Valiant 18.1 6 225.0 105 2.76 3.460 20.22 0 3 1 #> Merc 230 22.8 4 140.8 95 3.92 3.150 22.90 0 4 2 #> Merc 280C 17.8 6 167.6 123 3.92 3.440 18.90 0 4 4 #> Merc 450SE 16.4 8 275.8 180 3.07 4.070 17.40 0 3 3 #> Merc 450SL 17.3 8 275.8 180 3.07 3.730 17.60 0 3 3 #> Toyota Corolla 33.9 4 71.1 65 4.22 1.835 19.90 1 4 1 #> Toyota Corona 21.5 4 120.1 97 3.70 2.465 20.01 0 3 1 #> Dodge Challenger 15.5 8 318.0 150 2.76 3.520 16.87 0 3 2 #> AMC Javelin 15.2 8 304.0 150 3.15 3.435 17.30 0 3 2 #> Camaro Z28 13.3 8 350.0 245 3.73 3.840 15.41 0 3 4 #> Pontiac Firebird 19.2 8 400.0 175 3.08 3.845 17.05 0 3 2 #> Fiat X1-9 27.3 4 79.0 66 4.08 1.935 18.90 1 4 1 #> Porsche 914-2 26.0 4 120.3 91 4.43 2.140 16.70 1 5 2 #> Lotus Europa 30.4 4 95.1 113 3.77 1.513 16.90 1 5 2 #> Ford Pantera L 15.8 8 351.0 264 4.22 3.170 14.50 1 5 4 #> Volvo 142E 21.4 4 121.0 109 4.11 2.780 18.60 1 4 2 #> #> $individus_restants #> [1] 1 2 3 5 6 9 11 12 13 20 21 22 23 24 25 26 27 28 29 32 #> #> $variables_restantes #> [1] 1 2 3 4 5 6 7 9 10 11 #>
