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Found 5 papers, 1 papers with code
Regularization for Shuffled Data Problems via Exponential Family Priors on the Permutation Group
In the analysis of data sets consisting of (X, Y)-pairs, a tacit assumption is that each pair corresponds to the same observation unit.
Predicting Census Survey Response Rates With Parsimonious Additive Models and Structured Interactions
We discuss and interpret findings from our model on the US Census Planning Database.
A Pseudo-Likelihood Approach to Linear Regression with Partially Shuffled Data
In this paper, we present a method to adjust for such mismatches under ``partial shuffling" in which a sufficiently large fraction of (predictors, response)-pairs are observed in their correct correspondence.
A Two-Stage Approach to Multivariate Linear Regression with Sparsely Mismatched Data
A tacit assumption in linear regression is that (response, predictor)-pairs correspond to identical observational units.
Linear Regression with Sparsely Permuted Data
In this paper, we consider the situation of "permuted data" in which this basic correspondence has been lost.
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