Tags: #math #squares #curve
In this post:
- Fit a curve of degree N to a data set, getting data points 1 at a time.
- Storage Required: 3*N+2 values.
- Update Complexity: roughly 3*N+2 additions and multiplies.
- Finalize Complexity: Inverting a (N+1)x(N+1) matrix and multiplying by a vector to get polynomial coefficients.
- Simple C++ code and HTML5 demo at bottom!
http://blog.demofox.org/2016/12/22/incremental-least-squares-curve-fitting/
In this post:
- Fit a curve of degree N to a data set, getting data points 1 at a time.
- Storage Required: 3*N+2 values.
- Update Complexity: roughly 3*N+2 additions and multiplies.
- Finalize Complexity: Inverting a (N+1)x(N+1) matrix and multiplying by a vector to get polynomial coefficients.
- Simple C++ code and HTML5 demo at bottom!
http://blog.demofox.org/2016/12/22/incremental-least-squares-curve-fitting/
The blog at the bottom of the sea
Incremental Least Squares Curve Fitting
This Post In Short: Fit a curve of degree N to a data set, getting data points 1 at a time. Storage Required: 3*N+2 values. Update Complexity: roughly 3*N+2 additions and multiplies. Finalize Compl…
Tags: #squares #surfaces #volume #math
"This post generalizes that process to equations of any dimension such as z=f(x,y), w=f(x,y,z) or greater."
http://blog.demofox.org/2017/01/02/incremental-least-squares-surface-and-hyper-volume-fitting/
"This post generalizes that process to equations of any dimension such as z=f(x,y), w=f(x,y,z) or greater."
http://blog.demofox.org/2017/01/02/incremental-least-squares-surface-and-hyper-volume-fitting/
The blog at the bottom of the sea
Incremental Least Squares Surface and Hyper-Volume Fitting
The last post showed how to fit a $latex y=f(x)$ equation to a set of 2d data points, using least squares fitting. It allowed you to do this getting only one data point at a time, and still come up…