find.theta: Compute the SSM vector of parameters.
In peterrobertcurtis/SSM: Fit and Analyze Smooth Supersaturated Models

Description Usage Arguments Value

This function is called by fit.ssm to compute the coefficient vector that interpolates the data and minimises the smoothness of the resulting model.

1	find.theta(response, K, design_model, tol = .Machine$double.eps)

`response`	An length n vector. The observed responses.
`K`	A semi-positive definite N x N matrix that defines the smoothing criterion.
`design_model`	The n x N design model matrix.
`tol`	(optional) The model fitting requires the inversion of a large matrix and if the model basis is too large there can be numerical issues. This argument is passed on to `solve` so models can be fit despite these issues.