Synthesis by linear regression after transformation of a dependent variable
Generates univariate synthetic data using linear regression
of an outcome variable transformed by natural logarithm (lognorm),
square root (sqrtnorm) or cube root (cubertnorm).
syn.lognorm(y, x, xp, proper = FALSE, ...) syn.sqrtnorm(y, x, xp, proper = FALSE, ...) syn.cubertnorm(y, x, xp, proper = FALSE, ...)
y |
an original data vector of length |
x |
a matrix ( |
xp |
a matrix ( |
proper |
a logical value specifying whether proper synthesis should be conducted. See details. |
... |
additional parameters. |
Generates synthetic values using the spread around the
fitted linear regression line of transformed y given x.
For proper synthesis first the regression coefficients are drawn
from normal distribution with mean and variance from the fitted model.
The synthetic values are transformed back to the original scale.
A list with two components:
res |
a vector of length |
fit |
a data frame with regression coefficients and error estimates. |
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