Related Experiment Video
Updated: Feb 7, 2026

Experimental Manipulation of Body Size to Estimate Morphological Scaling Relationships in Drosophila
Published on: October 1, 2011
Wavelet regression: An approach for undertaking multi-time scale analyses of hydro-climate relationships
Jianhua Xu1,2
1Key Laboratory of Geographic Information Science (Ministry of Education), School of Geographic Sciences, East China Normal University, Shanghai, 200241, China.
Abstract:
Previous studies showed that hydro-climate processes are stochastic and complex systems, and it is difficult to discover the hidden patterns in the and non-stationary data and thoroughly understand the hydro-climate relationships. For the purpose to show multi-time scale responses of a hydrological variable to climate change, we developed an integrated approach by combining wavelet analysis and regression method, which is called wavelet regression (WR). The customization and the advantage of this approach over the existing methods are presented below: •The patterns in the data series of a hydrological variable and its related climatic factors are revealed by the wavelet analysis at different time scales.•The hydro-climate relationship of each pattern is revealed by the regression method based on the results of wavelet analysis.•The advantage of this approach over the existing methods is that the approach provides a routing to discover the hidden patterns in the stochastic and non-stationary data and quantitatively describe the hydro-climate relationships at different time scales.
Related Concept Videos
Regression Toward the Mean
Global Climate Change
What is Climate?
Multiple Regression
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
Relationship Formation
Correlation and Regression

