inca-package {inca} | R Documentation |
Specific functions are provided for rounding real weights to integers and performing an integer programming algorithm for calibration problems
Package: | inca |
Type: | Package |
Version: | 2018-02-09 |
Date: | 0.0.3 |
License: | GPL (>= 2) |
Calibration forces the weighted estimates of calibration variables to match known totals. This improves the quality of the design-weighted estimates. It is used to adjust for non-response and/or under-coverage. The commonly used methods of calibration produce non-integer weights. In cases where weighted estimates must be integers, one must "integerize" the calibrated weights. However, this procedure often produces final weights that are very different for the "sample" weights. To counter this problem, the *inca* package provides specific functions for rounding real weights to integers, and performing an integer programming algorithm for calibration problems with integer weights.
For a complete list of exported functions, use library(help = "inca")
.
Luca Sartore luca.sartore@nass.usda.gov and Kelly Toppin kelly.toppin@nass.usda.gov
Maintainer: Luca Sartore drwolf85@gmail.com
Theberge, A. (1999). Extensions of calibration estimators in survey sampling. Journal of the American Statistical Association, 94(446), 635-644.
Little, R. J., & Vartivarian, S. (2003). On weighting the rates in non-response weights. Kish, L. (1992). Weighting for unequal Pi. Journal of Official Statistics, 8(2), 183.
Rao, J. N. K., & Singh, A. C. (1997). A ridge-shrinkage method for range-restricted weight calibration in survey sampling. In Proceedings of the section on survey research methods (pp. 57-65). American Statistical Association Washington, DC.
Horvitz, D. G., & Thompson, D. J. (1952). A generalization of sampling without replacement from a finite universe. Journal of the American Statistical Association, 47(260), 663-685.
Horvitz, D. G., & Thompson, D. J. (1952). A generalization of sampling without replacement from a finite universe. Journal of the American Statistical Association, 47(260), 663-685.
Kalton, G., & Flores-Cervantes, I. (2003). Weighting methods. Journal of Official Statistics, 19(2), 81-98.
library(inca)