Sensitivity Analysis of Quality Assurance Using the Spatial Regression Approach—A Case Study of the Maximum/Minimum Air Temperature

By K. Hubbard, J. You. 2005

70 citations recorded by the source corpus.

Subfields: Civil and Structural Engineering, Environmental Engineering, Water Science and Technology

View Paper: https://www.semanticscholar.org/paper/6105ed92180c88ac16924bf8a97adf589b8482b0

How researchers see this paper

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

In Civil and Structural Engineering

1. Chengdong Xu
2. Jinfeng Wang
3. Qingxiang Li
4. Maogui Hu

In Environmental Engineering

1. Chengdong Xu
2. Jinfeng Wang
3. Qingxiang Li
4. Maogui Hu

In Water Science and Technology

1. Chengdong Xu
2. Jinfeng Wang
3. Qingxiang Li
4. Maogui Hu

Citations in the corpus

• Interpolation of Missing Temperature Data at Meteorological Stations Using P-BSHADE (2013, methodology): “The spatial regression test (SRT) (Hubbard and You 2005a; Hubbard et al. 2005) uses neighboring stations to estimate the measurement at the station of interest, and then the value of target station is calculated by the weighted average of the estimates.”
• Comprehensive Automated Quality Assurance of Daily Surface Observations (2010, methodology): “The size of the regression window and radius within which neighbors are selected are consistent with the sensitivity studies of Hubbard and You (2005).”