Description Usage Arguments Value Author(s) References Examples

Imputes the missing values of a list of matrices produced by `ahp.mat`

using the methods and assumptions made in \insertCiteHarker1987;textualahpsurvey. Missing values must be coded as `NA`

. As suggested in \insertCiteHarker1987;textualahpsurvey, a minimum of n-1 comparisons must be made, where n is the number of attributes (assuming that the decision-maker is perfectly consistent). Note that the algorithm assumes that the NA values will be imputed under perfect consistency with the other pairwise comparisons made.

1 | ```
ahp.missing(ahpmat, atts, round = FALSE, limit = FALSE)
``` |

`ahpmat` |
A list of pairwise comparison matrices of each decision maker generated by |

`atts` |
A list of attributes in the correct order |

`round` |
Rounds the imputation values of the matrix to the nearest integer if |

`limit` |
If set to |

A list of matrices with all `NA`

values imputed.

Frankie Cho

1 2 3 4 5 6 7 8 9 10 11 12 13 14 | ```
library(magrittr)
atts <- c('cult', 'fam', 'house', 'jobs', 'trans')
data(city200)
set.seed(42)
## Make a dataframe that is missing at random
missing.df <- city200[1:10,]
for (i in 1:10){
missing.df[i, round(stats::runif(1,1,10))] <- NA
}
missingahp <- ahp.mat(missing.df, atts, negconvert = TRUE)
ahp.missing(missingahp, atts)
``` |

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