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Concept

Imputation (statistics)

Related publications (26)

System identification via nuclear norm regularization for simulated moving bed processes from incomplete data sets

Colin Neil Jones

The application of nuclear norm regularization to system identification was recently shown to be a useful method for identifying low order linear models. In this paper, we consider nuclear norm regularization for identification of simulated moving bed proc ...

IEEE2009

System identification with missing data via nuclear norm regularization

Colin Neil Jones

2009

Model-free data interpretation for continuous monitoring of complex structures

Structural Health Monitoring (SMH) has the potential to provide reliable, quantitative data on the real condition of structures. Early detection of damage or deterioration can enable preventive repair and reduce maintenance costs. Although obtaining data f ...

EPFL2009

Iterative rigid body transformation estimation for visual 3-D object tracking

Aude Billard, Micha Hersch

We present a novel yet simple 3D stereo vision tracking algorithm which computes the position and orientation of an object from the location of markers attached to the object. The novelty of this algorithm is that it does not assume that the markers are tr ...

2008

Resamping variance estimation in surveys with missing data

Anthony Christopher Davison, Sylvain Sardy

We discuss variance estimation by resampling in surveys in which data are missing. We derive a formula for jackknife linearization in the case of calibrated estimation with deterministic regression imputation, and compare the resulting variance estimates w ...

2007

Reliable confidence intervals in quantitative genetics: Narrow-sense heritability

Anthony Christopher Davison

Many quantitative genetic statistics are functions of variance components, for which a large number of replicates is needed for precise estimates and reliable measures of uncertainty, on which sound interpretation depends. Moreover, in large experiments th ...

2007