xpca
Implementations of extended PCA methods, such as IPCA and EWMPCA.
Installation
pip install xpca
Paper
See Iterated and exponentially weighted moving principal component analysis on SSRN: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3913940
Usage
import xpca
Iterated PCA (IPCA)
# df is a pandas DataFrame first_year = 2008; last_year = 2020 Z_periods_ipca = [] model = xpca.IPCA() for period in [str(x) for x in range(first_year, last_year+1)]: df_period = df.loc[period] model.fit(df_period) Z_period = model.transform(df_period) Z_periods_ipca.append(Z_period) Z_periods_ipca = np.vstack(Z_periods_ipca)
Exponentially weighted moving PCA (EWMPCA)
xs = df.values ewmpca = xpca.EWMPCA(alpha=.9305) zs_ewmpca = ewmpca.add_all(xs)