Description Usage Arguments Details Value References Examples

Create simulated dataset from a multivariate normal. Used to recreate data simulations from Ehrlinger and Ishwaran (2012).

1 2 | ```
mvnorm.l2boost(n = 100, p = 100, beta = NULL, which.beta = NULL,
rho = 0)
``` |

`n` |
number of observations |

`p` |
number of coordinate directions in the design matrix |

`beta` |
a "true" beta vector of length p (default=NULL) See details. |

`which.beta` |
indicator vector for which beta coefficients to include as signal in simulation (default=NULL) see details |

`rho` |
correlation coefficient between coordinate directions |

By default, mvnorm.l2boost creates a data set of n multivariate normal random observations of p covariates
(see MASS:mvrnorm). The correlation matrix is constructed with 1 on the diagonals and the correlation
coefficient *rho* on the off diagonals.

The response is constructed as follows: If a true beta vector is not supplied, the first 10 beta coefficients carry
the signal with a value of 5, and the remaining p-10 values are set to zero. Given a *beta.true* vector, all
values are used as specified. The coefficent vector is truncated to have *p* signal terms if
length(*beta.true*) > *p*, and noise coordinates are added if length(*beta.true*) < *p*.

It is possible to pass an indicator vector *which.beta* to select specific signal elements from the
full vector *beta.true*.

call Matched function call

x design matrix of size

*n*x*p*y response vector of length

*n*

Ehrlinger J., and Ishwaran H. (2012). "Characterizing l2boosting" *Ann. Statist.*, 40 (2), 1074-1101

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | ```
#--------------------------------------------------------------------------
# Example: Multivariate normal data simulation
# Create a (reproducable) data set of size 100 x 100
set.seed(1024)
n<- 100
p<- 100
# Set 10 signal variables using a uniform beta=5, the remaining (p-10)=90 are
# set to zero indicating random noise.
beta <- c(rep(5,10), rep(0,p-10))
# Example with orthogonal design matrix columns (orthogonal + noise)
ortho.data <- mvnorm.l2boost(n, p, beta)
cbind(ortho.data$y[1:5],ortho.data$x[1:5,])
# Example with correlation between design matrix columns
corr.data <- mvnorm.l2boost(n, p, beta, rho=0.65)
cbind(corr.data$y[1:5],corr.data$x[1:5,])
``` |

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.