Description Usage Arguments Value Examples

Create correlated data

1 2 | ```
genCorData(n, mu, sigma, corMatrix = NULL, rho, corstr = "ind",
cnames = NULL, idname = "id")
``` |

`n` |
Number of observations |

`mu` |
A vector of means. The length of mu must be nvars. |

`sigma` |
Standard deviation of variables. If standard deviation differs for each variable, enter as a vector with the same length as the mean vector mu. If the standard deviation is constant across variables, as single value can be entered. |

`corMatrix` |
Correlation matrix can be entered directly. It must be symmetrical and positive semi-definite. It is not a required field; if a matrix is not provided, then a structure and correlation coefficient rho must be specified. |

`rho` |
Correlation coefficient, -1 <= rho <= 1. Use if corMatrix is not provided. |

`corstr` |
Correlation structure of the variance-covariance matrix defined by sigma and rho. Options include "ind" for an independence structure, "cs" for a compound symmetry structure, and "ar1" for an autoregressive structure. |

`cnames` |
Explicit column names. A single string with names separated by commas. If no string is provided, the default names will be V#, where # represents the column. |

`idname` |
The name of the index id name. Defaults to "id." |

A data.table with n rows and the k + 1 columns, where k is the number of means in the vector mu.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | ```
mu <- c(3, 8, 15)
sigma <- c(1, 2, 3)
corMat <- matrix(c(1, .2, .8, .2, 1, .6, .8, .6, 1), nrow = 3)
dtcor1 <- genCorData(1000, mu = mu, sigma = sigma, rho = .7, corstr = "cs")
dtcor2 <- genCorData(1000, mu = mu, sigma = sigma, corMatrix = corMat)
dtcor1
dtcor2
round(var(dtcor1[,.(V1, V2, V3)]), 3)
round(cor(dtcor1[,.(V1, V2, V3)]), 2)
round(var(dtcor2[,.(V1, V2, V3)]), 3)
round(cor(dtcor2[,.(V1, V2, V3)]), 2)
``` |

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