Description Usage Arguments Details Value See Also Examples

View source: R/MultiLambdaCVfun.R

Creates list of (unscaled) sample covariance matrices `X_b %*% t(X_b)`

for data blocks b = 1,..., B.

1 | ```
createXXblocks(datablocks, datablocksnew = NULL, which2pair = NULL)
``` |

`datablocks` |
List of data frames or matrices |

`datablocksnew` |
List of data frames or matrices |

`which2pair` |
Integer vector of size 2 (or |

The efficiency of `multiridge`

for high-dimendional data relies largely on this function:
all iterative calculation are performed on the out put of this function, which contains `B`

blocks of
`nxn`

matrices. If `which2pair != NULL`

, the function adds a paired covariance block, pairing the two data blocks corresponding to the elements of `which2pair`

. If predictions for new samples are desired, one also needs to specify
`datablocksnew`

, which should have he exact same format as `datablocks`

with matching column dimension (number of variables).

List. Same number of component as `datablocks`

when `which2pair = NULL`

, or augmented with one paired data block.
Dimension is `nxn`

for all components.

`createXblocks`

, which is required when parameter estimates are desired (not needed for prediction). A full demo and data are available from:

https://drive.google.com/open?id=1NUfeOtN8-KZ8A2HZzveG506nBwgW64e4

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | ```
#Example
#Simulate
Xbl1 <- matrix(rnorm(1000),nrow=10)
Xbl2 <- matrix(rnorm(2000),nrow=10)
#check whether dimensions are correct
ncol(Xbl1)==nrow(Xbl2)
#create cross-product
XXbl <- createXXblocks(list(Xbl1,Xbl2))
#suppose penalties for two data types equal 5,10, respectively
Sigma <- SigmaFromBlocks(XXbl,c(5,10))
#check dimensions (should be n x n)
dim(Sigma)
``` |

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