IpsoExtra: Extended variant of RegSDCipso

In RegSDC: Information Preserving Regression-Based Tools for Statistical Disclosure Control

Extended variant of RegSDCipso

Description

Possible to generate several y's and to re-scale residuals. Regression fitting by a sparse matrix algorithm is also possible (see reference).

Usage

IpsoExtra(
  y,
  x = NULL,
  ensureIntercept = TRUE,
  returnParts = FALSE,
  nRep = 1,
  resScale = NULL,
  digits = 9,
  rmse = NULL,
  sparseLimit = 500,
  printInc = TRUE
)

Arguments

y	Matrix of confidential variables
x	Matrix of non-confidential variables
ensureIntercept	Whether to ensure/include a constant term. Non-NULL x is subjected to EnsureIntercept
returnParts	Alternative output two matrices: yHat (fitted) and yRes (generated residuals).
nRep	Integer, when >1, several y's will be generated. Extra columns in output.
resScale	Residuals will be scaled by resScale
digits	Digits used to detect perfect fit (caused by fitted values as input). This checking will be done only when rmse is in input. When perfect fit, rmse will be used instead of resScale.
rmse	Desired root mean square error (residual standard error). Will be used when resScale is NULL or cannot be used (see parameter digits). This parameter forces the rmse value for one y variable (the first).
sparseLimit	Limit for the number of rows of a reduced x-matrix within the algorithm. When exceeded, a sparse algorithm is used (see reference).

Value

Generated version of y

Author(s)

Øyvind Langsrud

References

Douglas Bates and R Development Core Team (2022), Comparing Least Squares Calculations, R Vignette, vignette("Comparisons", package="Matrix").

Examples

x <- matrix(1:5, 5, 1)
y <- matrix(10 * (sample(7:39, 15) + 4 * (1:15)), 5, 3)
colnames(y) <- paste("y", 1:3, sep = "")
y1 <- y[, 1, drop = FALSE]

IpsoExtra(y, x)  # Same as RegSDCipso(y, x)

IpsoExtra(y, x, resScale = 0)  # Fitted values (whole numbers in this case)
IpsoExtra(y, x, nRep = 2, resScale = 1e-05)  # Downscaled residuals 

ySynth <- IpsoExtra(y1, x, nRep = 2, rmse = 0.25)  # Downscaled residuals 
summary(lm(ySynth ~ x))  # Identical regression results with Residual standard error: 0.25

IpsoExtra(fitted(lm(y1 ~ x)), x, nRep = 2, resScale = 0.1)  # resScale no effect since perfect fit
IpsoExtra(fitted(lm(y1 ~ x)), x, nRep = 2, resScale = 0.1, rmse = 2)  # with warning

# Using data in the paper
IpsoExtra(RegSDCdata("sec7y"), RegSDCdata("sec7x"))  # Similar to Y*
IpsoExtra(RegSDCdata("sec7y"), RegSDCdata("sec7x"), rmse = 1)

RegSDC documentation built on Aug. 19, 2022, 9:08 a.m.