Description Details Slots References See Also Examples

A S4 class to represent ranking data

It is well understood that the ranking representation and ordering representation of ranking data can easily be confused. I thus use a S4 class to store all the information about the ranking data. This can avoid unnecessary confusion.

It is possible to store both complete and top-q rankings in the same RankData object. Three slots `topq`

, `subobs`

, and
`q_ind`

are introduced for this purpose. Note that there is generally no need to specify these slots if your data set only contains
a single "q" level (for example all data are top-10 rankings). The "q" level for complete ranking should be `nobj-1`

.
Moreover, if the rankings are organized in chunks of increasing "q" levels (for
example, top-2 rankings followed by top-3 rankings followed by top-5 rankings etc.), then slots `subobs`

, and `q_ind`

can also be inferred
correctly by the initializer. Therefore it is highly recommender that you organise the ranking matrix in this way and utilize the initializer.

`nobj`

The number of ranked objects. If not provided, it will be inferred as the maximum ranking in the data set. As a result, it must be provided if the data is top-q ranking.

`nobs`

the number of observations. No need to be provided during initialization since it must be equal to the sum of slot

`count`

.`ndistinct`

the number of distinct rankings. No need to be provided during initialization since it must be equal to the number of rows of slot

`ranking`

.`ranking`

a matrix that stores the ranking representation of distinct rankings. Each row contains one ranking. For top-q ranking, all unobserved objects have ranking

`q+1`

.`count`

the number of observations for each distinct ranking corresponding to each row of

`ranking`

.`topq`

a numeric vector to store top-q ranking information. More information in details section.

`subobs`

a numeric vector to store number of observations for each chunk of top-q rankings.

`q_ind`

a numeric vector to store the beginning and ending of each chunk of top-q rankings. The last element has to be

`ndistinct+1`

.

Qian Z, Yu L. H. P (2019) "Weighted Distance-Based Models for Ranking Data Using the R Package rankdist." *Journal of Statistical Software*, **90**(5), 1-31. doi: 10.18637/jss.v090.i05

1 2 3 4 5 6 7 8 9 10 | ```
# creating a data set with only complete rankings
rankmat <- replicate(10,sample(1:52,52), simplify = "array")
countvec <- sample(1:52,52,replace=TRUE)
rankdat <- new("RankData",ranking=rankmat,count=countvec)
# creating a data set with both complete and top-10 rankings
rankmat_in <- replicate(10,sample(1:52,52), simplify = "array")
rankmat_in[rankmat_in>11] <- 11
rankmat_total <- cbind(rankmat_in, rankmat)
countvec_total <- c(countvec,countvec)
rankdat2 <- new("RankData",ranking=rankmat_total,count=countvec_total, nobj=52, topq=c(10,51))
``` |

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