A Python implementation of the Backfit algorithm for fitting to Generalized Additive Models
Python Implementation of the Backfit algorithm described by Wood, Simon. (2017). Generalized Additive Models: an introduction with R (CRC Press).
USAGE: yr, alpha = GAMapply(X,mod,pp,hdr,Y).
INPUT: (works with pandas dataframes only) X = N x d dataframe, Environmental inputs or corelates; this variable should be standardized. mod = list() data type of Cubic spline fits to each column in X. Y = N x 1, instrument response pp = polynomial fit to mass 18, not presently implemented. hdr = column names to subindex.
OUTPUT: yr = reconstructed series of y from the model. alpha = mean of y. This should be zero if already standardized.
DISCLAIMER: Provided "as is" without warranty of any kind.