CV2se+se2CV+CV2mse+mse2CV | R Documentation |

Calculates the standard error or the mean squared error from a given CV and vice versa for log-normal data.

CV2se(CV) se2CV(se) CV2mse(CV) mse2CV(mse)

`CV` |
coefficient of variatio as ratio (not percent) |

`se` |
standard error |

`mse` |
mean squared error (aka residual variance) |

Returns

` se = sqrt(log(CV^2+1))`

` CV = sqrt(exp(se^2)-1)`

` mse = log(CV^2+1)`

` CV = sqrt(exp(mse)-1)`

These functions were originally intended for internal use only but may be useful for others.

D. Labes

# these functions are one liners: CV2se <- function(CV) return(sqrt(log(1.0 + CV^2))) se2CV <- function(se) return(sqrt(exp(se^2)-1)) CV2se(0.3) # should give: # [1] 0.2935604 se2CV(0.2935604) # [1] 0.3

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