I am trying to estimate missing values in time-series data which is in the form of a matrix. The columns represent the time points,i.e. Now, I want to fit each row of the matrix to a B-Spline, and use it to estimate the missing values. I could fit the data to a normal spline using MATLAB, but I am completely stuck at trying to figure out how to fit the data to create a B-Spline. Using the default bspline function in the Curve Fitting Toolbox lets me set the knot vector to the vector of time points, but I cannot set the control points, i.e. the elements of the row.
Any help would be much appreciated.
EDIT: EXAMPLE ADDED
The time-series data has rows that look like this:
-0.11 0.1 0.01 0.06 0.04 -0.26 0.04 0.19 -0.22 -0.2 0.12 0.21 -0.26 -0.3 0.22 0.58 -0.36 0.13
My knot vector is basically the time points, and it looks like this:
0 7 14 21 28 35 42 49 56 63 70 77 84 91 98 105 112 119
Basically I want to use each row along with the knot vector to construct a B-Spline.
