In this paper we give a proof of convergence of the iterative proportional fitting procedures (IPFP). The IPFP has been proposed by Deming and Stephan (1940) to estimate cell probabilities in contingency tables subject to certain marginal constraints. A proof of convergence has been given in the finite discrete case by several authors around 1970. The convergence properties of the IPFP in the general (non-discrete) case remained an open problem since then. (orig.)Available from TIB Hannover: RO 7057(1993,4) / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekSIGLEDEGerman
ABSTRACT. In this paper we discuss the process of building a joint probability distribution from an ...
summary:In this paper we analyze the asymptotic behavior of the IPF algorithm for the problem of fin...
There are many numerical procedures for calculating the maximum likelihood estimates for loglinear m...
The asymptotic behavior of the iterative proportional fitting procedure (IPF procedure) is analyzed ...
The iterative proportional fitting procedure (IPF procedure) alternately fits a given nonnegative ma...
Convergence of the Iterative Proportional Fitting procedure is analyzed. The input comprises a nonne...
A new analysis of the Iterative Proportional Fitting procedure is presented. The input data consist ...
A new analysis of the Iterative Proportional Fitting procedure is presented. The input data consist ...
Iterative proportional fitting (IPF) is a calibration technique for estimating cell frequencies of a...
Convergence of the Iterative Proportional Fitting procedure is analyzed. The input comprises a nonne...
This paper proves continuity of f-projections and the continuous dependence of the limit matrix of t...
Iterative proportional fitting (IPF) is described formally and historically and its advantages and l...
International audienceThe iterative proportional fitting procedure (IPFP), introduced in 1937 by Kru...
AbstractA Gaussian version of the iterative proportional fitting procedure (IFP-P) was applied by Sp...
A Gaussian version of the iterative proportional fitting procedure (IFP-P) was applied by Speed and ...
ABSTRACT. In this paper we discuss the process of building a joint probability distribution from an ...
summary:In this paper we analyze the asymptotic behavior of the IPF algorithm for the problem of fin...
There are many numerical procedures for calculating the maximum likelihood estimates for loglinear m...
The asymptotic behavior of the iterative proportional fitting procedure (IPF procedure) is analyzed ...
The iterative proportional fitting procedure (IPF procedure) alternately fits a given nonnegative ma...
Convergence of the Iterative Proportional Fitting procedure is analyzed. The input comprises a nonne...
A new analysis of the Iterative Proportional Fitting procedure is presented. The input data consist ...
A new analysis of the Iterative Proportional Fitting procedure is presented. The input data consist ...
Iterative proportional fitting (IPF) is a calibration technique for estimating cell frequencies of a...
Convergence of the Iterative Proportional Fitting procedure is analyzed. The input comprises a nonne...
This paper proves continuity of f-projections and the continuous dependence of the limit matrix of t...
Iterative proportional fitting (IPF) is described formally and historically and its advantages and l...
International audienceThe iterative proportional fitting procedure (IPFP), introduced in 1937 by Kru...
AbstractA Gaussian version of the iterative proportional fitting procedure (IFP-P) was applied by Sp...
A Gaussian version of the iterative proportional fitting procedure (IFP-P) was applied by Speed and ...
ABSTRACT. In this paper we discuss the process of building a joint probability distribution from an ...
summary:In this paper we analyze the asymptotic behavior of the IPF algorithm for the problem of fin...
There are many numerical procedures for calculating the maximum likelihood estimates for loglinear m...