Conversion between Representations of Responses or States

Converts between binary matrix and pattern representations of response patterns or knowledge states.

as.pattern(R, freq = FALSE, useNames = FALSE, as.set = FALSE,
           sep = "", emptyset = "{}", as.letters = NULL)

as.binmat(N.R, uniq = TRUE, col.names = NULL, as.logical = FALSE)

is.subset(R)

Arguments

R

an indicator matrix of response patterns or knowledge states.

N.R

either a (named) vector of absolute frequencies of response patterns; or a character vector of response patterns or knowledge states; or a set of sets representing the knowledge structure.

freq

logical, should the frequencies of response patterns be reported?

uniq

logical, if TRUE, only the unique response patterns are returned.

useNames

logical, return response patterns as combinations of item names.

as.set

logical, return response patterns as set of sets.

sep

character to separate the item names.

emptyset

string representing the empty set if useNames is TRUE.

as.letters

deprecated, use useNames instead.

col.names

column names for the state or response matrix.

as.logical

logical, return logical matrix of states.

Value

as.pattern returns a vector of integers named by the response patterns if freq is TRUE, else a character vector. If

as.set is TRUE, the return value is of class set.

as.binmat returns an indicator matrix. If as.logical is

TRUE, it returns a logical matrix.

is.subset returns a logical incidence matrix of the subset relation among states.

See also

blim, set in package sets.

Examples

data(DoignonFalmagne7)
K <- DoignonFalmagne7$K
as.pattern(K, freq = TRUE)
#> 00000 01000 10000 11000 11010 11100 11101 11110 11111 
#>     1     1     1     1     1     1     1     1     1 
as.pattern(K)
#> [1] "00000" "10000" "01000" "11000" "11100" "11010" "11110" "11101" "11111"
as.pattern(K, useNames = TRUE)
#> [1] "{}"    "a"     "b"     "ab"    "abc"   "abd"   "abcd"  "abce"  "abcde"
as.pattern(K, as.set = TRUE)
#> {{}, {"a"}, {"b"}, {"a", "b"}, {"a", "b", "c"}, {"a", "b", "d"}, {"a",
#>  "b", "c", "d"}, {"a", "b", "c", "e"}, {"a", "b", "c", "d", "e"}}

N.R <- DoignonFalmagne7$N.R
dim(as.binmat(N.R))
#> [1] 32  5
dim(as.binmat(N.R, uniq = FALSE))
#> [1] 1000    5

## Knowledge structure as binary matrix
as.binmat(c("000", "100", "101", "111"))
#>      a b c
#> [1,] 0 0 0
#> [2,] 1 0 0
#> [3,] 1 0 1
#> [4,] 1 1 1
as.binmat(set(set(), set("a"), set("a", "c"), set("a", "b", "c")))
#>      a b c
#> [1,] 0 0 0
#> [2,] 1 0 0
#> [3,] 1 0 1
#> [4,] 1 1 1
as.binmat(c("000", "100", "101", "111"), as.logical = TRUE)
#>          a     b     c
#> [1,] FALSE FALSE FALSE
#> [2,]  TRUE FALSE FALSE
#> [3,]  TRUE FALSE  TRUE
#> [4,]  TRUE  TRUE  TRUE

## Subset relation incidence matrix
is.subset(K)
#>        >
#> <       00000 10000 01000 11000 11100 11010 11110 11101 11111
#>   00000  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE
#>   10000 FALSE  TRUE FALSE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE
#>   01000 FALSE FALSE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE
#>   11000 FALSE FALSE FALSE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE
#>   11100 FALSE FALSE FALSE FALSE  TRUE FALSE  TRUE  TRUE  TRUE
#>   11010 FALSE FALSE FALSE FALSE FALSE  TRUE  TRUE FALSE  TRUE
#>   11110 FALSE FALSE FALSE FALSE FALSE FALSE  TRUE FALSE  TRUE
#>   11101 FALSE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE  TRUE
#>   11111 FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE

## Plotting the knowledge structure
if(requireNamespace("relations") &&
   requireNamespace("Rgraphviz")) {
  rownames(K) <- as.pattern(K, useNames = TRUE)
  plot(relations::as.relation(is.subset(K)), main = "")
}
#> Loading required namespace: relations
#> Loading required namespace: Rgraphviz