Recent content by Lindley

I want to use a Kalman filter to estimate the motion of an object. However, the catch is, the measurements I have only tell me that the object is somewhere along a particular line segment. Typically Kalman filters require normally distributed measurements. I'm trying to work out how best to...

I have a Gaussian distribution. I know the variance in the directions of the first and second eigenvectors (the directions of maximum and minimum radius of the corresponding ellipse at any fixed mahalnobis distance), and the direction of the first eigenvector. Is there a simple closed form...

As a computational geometry problem, I figured this was close enough.

I have two sets of line segments, A and B. My goal is, for each segment in A, I want to find all segments in B which approach within some threshold distance. Clearly this can be done in O(n^2) easily enough, but I think it's possible to do better. For instance, if I were working with points...

I only need straight lines. The parametric approach makes sense, thanks, I'll give that a try!

I have a simple problem. I have a set of 3D data points and I want to fit a line through them using linear least squares. I understand the basic approach required: set up two matrices such that Ax = b, then make it a square matrix A^t*Ax = A^t*b, then solve for x using a Cholesky decomposition...