Multivariate errors-in-variables model

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Closed-loop subspace identification of multivariable dynamic errors-in-variables models based on ORT

Cluster Computing, 2018
In terms of the model of errors-in-variables, this article analyses the causes of deviation based on the existing method of subspace identification in the closed-loop system; then, it puts forward another method of subspace identification with an auxiliary variable based on orthogonal decomposition.
Minghong She, Baocang Ding
openaire +1 more source

A googness of-fit-test for a multivariate errors-in-variables model

2009
A multivariate errors-in-variables model AX ??? B is considered, where the data matrices A and B are observed with errors, and a matrix parameter X is to be estimated. A goodness-of-???t test which is based on the moment estimator is constructed. The proposed test is asymptotically chi-squared under null hypothesis. The power of the test is discussed.
Kukush, A., Polekha, M.
openaire +1 more source

Combining the Frisch scheme and Yule-Walker equations for identifying multivariable errors-in-variables models

2010
Errors–in–Variables (EIV) models, i.e. models whose stochastic environment considers measurement errors on both inputs and outputs are intrinsically more realistic than representations assuming an exact knowledge of the input but are also more difficult to estimate.
DIVERSI, ROBERTO, GUIDORZI, ROBERTO
openaire +1 more source

Antibody–drug conjugates: Smart chemotherapy delivery across tumor histologies

Ca-A Cancer Journal for Clinicians, 2022
Paolo Tarantino +2 more
exaly

An overview of real‐world data sources for oncology and considerations for research

Ca-A Cancer Journal for Clinicians, 2022
Lynne Penberthy, Donna R Rivera, Jennifer L Lund, Msph +2 more
exaly

Admissibilities of linear estimator in a class of linear models with a multivariate t error variable