lpc(x::AbstractVector, p::Int, [LPCBurg()])
Given input signal
x and prediction order
p, returns IIR coefficients
a and average reconstruction error
prediction_err. Note that this method does NOT return the leading
1 present in the true autocorrelative estimate; it omits it as it is implicit in every LPC estimate, and must be manually reintroduced if the returned vector should be treated as a polynomial.
The algorithm used is determined by the last optional parameter, and can be either
lpc(x::AbstractVector, p::Int, LPCBurg())
LPC (Linear-Predictive-Code) estimation, using the Burg method. This function implements the mathematics published in .
 - Enhanced Partial Tracking Using Linear Prediction (DAFX 2003 article, Lagrange et al) http://www.sylvain-marchand.info/Publications/dafx03.pdf
lpc(x::AbstractVector, p::Int, LPCLevinson())
LPC (Linear-Predictive-Code) estimation, using the Levinson method. This function implements the mathematics described in .
 - The Wiener (RMS) Error Criterion in Filter Design and Prediction (N. Levinson, Studies in Applied Mathematics 25(1946), 261-278, https://doi.org/10.1002/sapm1946251261)