MaxContribution {GaussSuppression} R Documentation

## Find major contributions to aggregates

### Description

Assuming aggregates are calculated via a dummy matrix by z = t(x) %*% y, the n largest contributions are found (value or index) for each aggregate.

### Usage

MaxContribution(
x,
y,
n = 1,
decreasing = TRUE,
index = FALSE,
groups = NULL,
return2 = FALSE
)


### Arguments

 x A (sparse) dummy matrix y Vector of input values (contributors) n Number of contributors to be found decreasing Ordering parameter. Smallest contributors found when FALSE. index Indices to y returned when TRUE groups When non-NULL, major contributions after aggregation within groups. Cannot be combined with index = TRUE. The missing group category is excluded. return2 When TRUE, two matrices are returned, value and id. The latter contains indices when group is NULL and otherwise a character matrix of groups.

### Value

Matrix with lagest contributions in first column, second largest in second column and so on. Alternative output when using parameters index or return2.

### Author(s)

Ã˜yvind Langsrud

ModelMatrix

### Examples

library(SSBtools)

z <- SSBtoolsData("sprt_emp_withEU")
z$age[z$age == "Y15-29"] <- "young"
z$age[z$age == "Y30-64"] <- "old"

a <- ModelMatrix(z, formula = ~age + geo, crossTable = TRUE)

cbind(as.data.frame(a$crossTable), MaxContribution(a$modelMatrix, z$ths_per, 1)) cbind(a$crossTable, MaxContribution(a$modelMatrix, z$ths_per, 10))
cbind(a$crossTable, MaxContribution(a$modelMatrix, z$ths_per, 10, index = TRUE)) # Both types of output can be achieved with return2 = TRUE) identical(MaxContribution(a$modelMatrix, z$ths_per, 10, return2 = TRUE), list(value = MaxContribution(a$modelMatrix, z$ths_per, 10), id = MaxContribution(a$modelMatrix, z$ths_per, 10, index = TRUE))) b <- ModelMatrix(z[, -4], crossTable = TRUE, inputInOutput = c(TRUE, FALSE, TRUE)) k <- cbind(b$crossTable, MaxContribution(b$modelMatrix, z$ths_per, 10))

gr18 <- paste0("g", 1:18)                          # Each row is a group
k18 <- cbind(b$crossTable, MaxContribution(b$modelMatrix, z$ths_per, 10, groups = gr18)) identical(k, k18) # TRUE gr9 <- paste0("g", as.integer(10 * z$ths_per)%%10) # 9 groups from decimal
k9 <- cbind(b$crossTable, MaxContribution(b$modelMatrix, z$ths_per, 10, groups = gr9)) k18[c(4, 13, 17, 33), ] k9[c(4, 13, 17, 33), ] # Group info obtained with return2 = TRUE k9_id <- cbind(b$crossTable, MaxContribution(b$modelMatrix, z$ths_per, 10, groups = gr9,
return2 = TRUE)$id) k9_id[c(4, 13, 17, 33), ] # Verify similarity z$y <- z$ths_per + (1:nrow(z))/100 # to avoid equal values id1 <- MaxContribution(b$modelMatrix, z$y, 10, index = TRUE) id1[!is.na(id1)] <- paste0("g", id1[!is.na(id1)]) mc2 <- MaxContribution(b$modelMatrix, z$y, 10, groups = gr18, return2 = TRUE) id2 <- mc2$id
identical(id1, id2)



[Package GaussSuppression version 0.8.3 Index]