Maximum entropy and minimum cross-entropy estimation are applicable when faced with ill-posed estimation problems. I introduce a Stata command that estimates a probability distribution using a maximum entropy or minimum cross-entropy criterion. I show how this command can be used to calibrate survey data to various population totals.
DemingW. E., and StephanF. F.1940. On a least squares adjustment of a sample frequency table when the expected marginal totals are known. Annals of Mathematical Statistics11: 427–444.
2.
DevilleJ.-C., and SärndalC.-E.1992. Calibration estimators in survey sampling. Journal of the American Statistical Association87: 376–382.
3.
DevilleJ.-C., SärndalC.-E., and SautoryO.1993. Generalized raking procedures in survey sampling. Journal of the American Statistical Association88: 1013–1020.
4.
GolanA., JudgeG. G., and MillerD.1996. Maximum Entropy Econometrics: Robust Estimation with Limited Data.Chichester, UK: Wiley.
5.
JaynesE. T.1957. Information theory and statistical mechanics. Physical Review106: 620–630.
6.
MerzJ., and StolzeH.2008. Representative time use data and new harmonised calibration of the American Heritage Time Use Data 1965–1999. electronic International Journal of Time Use Research5: 90–126.
7.
MittelhammerR. C., JudgeG. G., and MillerD. J.2000. Econometric Foundations.Cambridge: Cambridge University Press.
