Order independence and factor convergence in iterative scaling
From MaRDI portal
Publication:686367
DOI10.1016/0024-3795(93)90218-DzbMath0776.60087MaRDI QIDQ686367
Jack B. Brown, Phillip J. Chase, Arthur O. Pittenger
Publication date: 13 October 1993
Published in: Linear Algebra and its Applications (Search for Journal in Brave)
Applications of Markov chains and discrete-time Markov processes on general state spaces (social mobility, learning theory, industrial processes, etc.) (60J20) Foundations of probability theory (60A99)
Related Items
Continuity of f-projections and applications to the iterative proportional fitting procedure, Accumulation points of the iterative proportional fitting procedure, Jack Brown -- in memoriam, Iterated Proportional Fitting Procedure and Infinite Products of Stochastic Matrices, Biproportional scaling of matrices and the iterative proportional fitting procedure, Doubly Stochastic Normalization of the Gaussian Kernel Is Robust to Heteroskedastic Noise
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- The rate of convergence of Sinkhorn balancing
- On Dykstra's iterative fitting procedure
- On pairs of multidimensional matrices
- An iterative procedure for obtaining I-projections onto the intersection of convex sets
- An extension of a theorem of Darroch and Ratcliff in loglinear models and its application to scaling multidimensional matrices
- Matrix scaling, entropy minimization, and conjugate duality. I: Existence conditions
- On the scaling of multidimensional matrices
- Scalings of matrices which have prespecified row sums and column sums via optimization
- Generalized scalings satisfying linear equations
- Non-negative matrices and Markov chains. 2nd ed
- D//\(1AD_ 2 \)theorems for multidimensional matrices
- I-divergence geometry of probability distributions and minimization problems
- A geometric interpretation of Darroch and Ratcliff's generalized iterative scaling
- Concerning nonnegative matrices and doubly stochastic matrices
- Approximating probability distributions to reduce storage requirements
- Convergence of the Iterative Scaling Procedure for Non-Negative Matrices
- Notes on the Birkhoff Algorithm for Doubly Stochastic Matrices
- The DAD Theorem for Arbitrary Row Sums
- The minimum discrimination information approach in analyzing categorical data
- Properties of Kruithof's Projection Method
- On the Optimum Rate of Transmitting Information
- A Relationship Between Arbitrary Positive Matrices and Doubly Stochastic Matrices
- Estimating Nonnegative Matrices from Marginal Data
- Maximum Entropy for Hypothesis Formulation, Especially for Multidimensional Contingency Tables
- Convex Sets of Non-Negative Matrices
- Contingency tables with given marginals
- Probability Densities with Given Marginals
- Diagonal Equivalence to Matrices with Prescribed Row and Column Sums
- An Iterative Procedure for Estimation in Contingency Tables
- Continuous Dependence of A in the D 1 AD 2 Theorems
- Generalized Iterative Scaling for Log-Linear Models
- A note on approximations to discrete probability distributions
- On a Least Squares Adjustment of a Sampled Frequency Table When the Expected Marginal Totals are Known
- On Information and Sufficiency
- An Iterative Method of Adjusting Sample Frequency Tables When Expected Marginal Totals are Known
