# VAF: Proportion of variance accounted for (VAF) for each block and... In RegularizedSCA: Regularized Simultaneous Component Based Data Integration

## Description

Proportion of variance accounted for (VAF) is calculated for each block and each column.

## Usage

 `1` ```VAF(DATA, Jk, R) ```

## Arguments

 `DATA` A matrix, which contains the concatenated data with the same subjects from multiple blocks. Note that each row represents a subject. `Jk` A vector containing number of variables in the concatinated data matrix. `R` Number of components (R>=2).

## Value

 `block` Proportion of VAF for each block. `component` Proportion of VAF for each component of each block.

## References

Schouteden, M., Van Deun, K., Wilderjans, T. F., & Van Mechelen, I. (2014). Performing DISCO-SCA to search for distinctive and common information in linked data. Behavior research methods, 46(2), 576-587.

Schouteden, M., Van Deun, K., Pattyn, S., & Van Mechelen, I. (2013). SCA with rotation to distinguish common and distinctive information in linked data. Behavior research methods, 45(3), 822-833.

## Examples

 ```1 2 3 4 5 6 7 8 9``` ```## Not run: DATA1 <- matrix(rnorm(50), nrow=5) DATA2 <- matrix(rnorm(100), nrow=5) DATA <- cbind(DATA1, DATA2) Jk <- c(10, 20) R <- 5 VAF(DATA, Jk, R) ## End(Not run) ```

### Example output

```\$block
 1 1

\$component
[,1]      [,2]      [,3]       [,4]       [,5]
[1,] 0.1748580 0.4190322 0.2663509 0.07454524 0.06521362
[2,] 0.3988056 0.2479239 0.1097642 0.12828075 0.11522556
```

RegularizedSCA documentation built on May 2, 2019, 8:24 a.m.