Kernel smoothing in R
Budget: $10 – $30 USD
Kernel smoothing in R is implemented by the ksmooth function. When applied to a time series, the problem with this smoother is that past smoothed values change as new input values are added.
We need an update to this function or a similar function that does not change past smoothed values as new input values are added.
ksmooth usesGaussian kernel, but any other kernel can be used that achieves similar results.
The deliverable for this project is a well-documented R code function that will take an input array (see attached) and output the smoothed values that do not change as new points are added. Input and smoothed line should be plotted.
We need an update to this function or a similar function that does not change past smoothed values as new input values are added.
ksmooth usesGaussian kernel, but any other kernel can be used that achieves similar results.
The deliverable for this project is a well-documented R code function that will take an input array (see attached) and output the smoothed values that do not change as new points are added. Input and smoothed line should be plotted.
Related categories:
Matlab and Mathematica
Statistics
Mathematics
R Programming Language
Statistical Analysis