Dealing with missing data

By Beata Walczak, D. Massart. 2001

161 citations recorded by the source corpus.

Subfields: Analytical Chemistry, Biophysics, Industrial and Manufacturing Engineering

View Paper: https://www.semanticscholar.org/paper/3648f379003ae179486a9c3ad0bbb8cb657f7a7e

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Analytical Chemistry

1. Bogdan Gabrys
2. Sibylle Strandt
3. Petr Kadlec

In Biophysics

1. Bogdan Gabrys
2. Sibylle Strandt
3. Petr Kadlec

In Industrial and Manufacturing Engineering

1. Bogdan Gabrys
2. Sibylle Strandt
3. Petr Kadlec

Citations in the corpus

• Data-driven Soft Sensors in the process industry (2009, methodology): “…takes into account the multivariate statistics of the data and thus makes the reconstruction of the missing values dependent on the other available variables of the affected samples (see e.g. Walczak and Massart (2001b) for maximum-likelihood multivariate approach to missing values replacement).”