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auxiliary explanatory variables vs explanatory auxiliary variables

A complete search of the internet has found that "explanatory auxiliary variables" is the most popular phrase on the web.

Last updated: May 08, 2026 • 7 views

More popular!

412 results on the web

"auxiliary explanatory variables"

Some examples from the web:

  • Jan 24, 2015 ... To implement a "Mundlak-Chamberlain" approach, you would need to calculate the auxiliary explanatory variables that they discuss, and then ...
  • ... auxiliary explanatory variables) is integrated into children's prior knowledge. Here we predict that children's prior beliefs and evidence should interact ...
  • ... auxiliary explanatory variables (squares and cross-products) you've just created: g.final<-lm(g.resid2~grade+exp+exp2+union+grade2+exp4+exp3+gradexp + ...
  • Additionally, grass height (Hgrass) and clover height (Hclover) were used as auxiliary explanatory variables with CSR to estimate forage yield and quality.
  • The texture data were used as auxiliary explanatory variables, as detailed in the data modeling section. 2.3. Data Acquisition with XRF and vis–NIR ...
  • ... auxiliary explanatory variables for soil moisture downscaling at the moment. Based on the above understanding, this study aims to employ three decision tree ...
  • The inclusion of auxiliary explanatory variables increased the prediction accuracy of MPS (R2 increased from 0.61 to 0.82), bulk density. (from 0.56 to 0.73), ...

97 results on the web

"explanatory auxiliary variables"

Some examples from the web:

  • Jul 10, 2021 ... ENGLISH, the use of the four most explanatory auxiliary variables enables to reduce the variance significantly, but adding more calibration ...
  • Mar 3, 2011 ... The lack/presence of units in the sample s, despite the addition of many explanatory auxiliary variables, can still be related to the target ...
  • Jan 18, 2024 ... Then, we enhance the model by introducing explanatory auxiliary variables, aiming to find the model closest to the parsimonious mean model, ...
  • addressed two primary issues of tourism demand forecasting with DL: data inaccessibility and the requirement of explanatory auxiliary variables (Zhang et al.,, ...
  • Jan 18, 2024 ... Then, we enhance the model by introducing explanatory auxiliary variables, aiming to find the model clos- est to the parsimonious mean model ...
  • Nov 28, 2022 ... For this purpose, to more closely match the actual data settings in terms of network size and the number of explanatory auxiliary variables ...

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