A kernel smoother is a statistical technique for estimating a real valued function by using its noisy observations, when no parametric model for this function is known. The estimated function is smooth, and the level of smoothness is set by a single parameter.
This technique is most appropriate for low dimensional (p < 3) data visualization purposes. Actually, the kernel smoother represents the set of irregular data points as a smooth line or surface.
Read more about Kernel Smoother: Definitions, Nearest Neighbor Smoother, Kernel Average Smoother, Local Linear Regression, Local Polynomial Regression
Famous quotes containing the words kernel and/or smoother:
“After night’s thunder far away had rolled
The fiery day had a kernel sweet of cold”
—Edward Thomas (1878–1917)
“For the lips of a loose woman drip honey, and her speech is smoother than oil; but in the end she is bitter as wormwood, sharp as a two-edged sword.”
—Bible: Hebrew, Proverbs 5:3.