Smoothing related to statistical programing solutions in which a signal is filtered to create an approximating function that attempts to capture important patterns in the data, while leaving out noise, or for visual clarity to see general trends.
I am trying to understand the different behaviors of these two smoothing functions when given apparently equivalent inputs. My understanding …
r regression smoothingI need to plot a smooth curve of best fit but all the methods I've found use scipy.optimize.curve_…
python curve-fitting spline smoothingOriginal question I want to smooth my explanatory variable, something like Speed data of a vehicle, and then use this …
r regression curve-fitting smoothingI have 19 points (x, y, z values) which can be joined up to produce a curve (very angular). Is there …
matlab interpolation curve-fitting smoothing cubicI have several data points which seem suitable for fitting a spline through them. When I do this, I get …
r regression curve-fitting spline smoothingSavitzky-Golay smoothing filter can be used to calculate the coefficients so as to calculate the smoothed y-values by applying the …
c++ smoothing derivativeIf I had an array of numbers such as [3, 5, 0, 8, 4, 2, 6], is there a way to “smooth out” the values so they’…
javascript arrays smoothing