Visual Studio Magazine15d
Random Neighborhoods Regression Using C#
Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of the random neighborhoods ...
IEEE1mon
Position Estimation Error Reduction Based on First-Order Complex-Coefficient Extended State Observer for IPMSM Sensorless Drives
To reduce the rotor position estimation errors, a first-order complex-coefficient extended state observer (CCF-ESO) with frequency-adaptive bandpass characteristic is proposed. Compared with the ...
Frontiers5mon
Nonlinear regression modeling of swelling characteristics in cracked expansive soil: integrating crack, moisture, density, and load effect
By comprehensively considering crack rate, dry density, initial moisture content, and overburden load, a nonlinear regression swelling model is proposed in this research. The degree of crack ...
LinkedIn1y
What are the advantages and disadvantages of trimming or winsorizing outliers in regression?
They can have a large impact on the estimation and interpretation of regression coefficients in linear ... such as M-estimation. Robust standard errors: Calculate reliable estimates despite ...
LinkedIn1y
How do you use regression analysis for forecasting and prediction?
One thing to consider is that, a standard ... Polynomial Regression: Models non-linear relationships by introducing polynomial terms while retaining linearity in coefficients.
Frontiers3y
Estimation of Health-Related Physical Fitness Using Multiple Linear Regression in Korean Adults: National Fitness Award 2015–2019
Therefore, our study aimed to develop a multiple linear regression model to predict HRPF parameters (e.g., HGS, flexibility, muscular endurance, and CRF) using easy-to-measure dependent variables [e.g ...