# filter¶

function for filtering

quantecon.filter.hamilton_filter(data, h, *args)[source]

This function applies “Hamilton filter” to the data

http://econweb.ucsd.edu/~jhamilto/hp.pdf

Parameters: data : arrray or dataframe h : integer Time horizon that we are likely to predict incorrectly. Original paper recommends 2 for annual data, 8 for quarterly data, 24 for monthly data. *args : integer If supplied, it is p in the paper. Number of lags in regression. Must be greater than h. If not supplied, random walk process is assumed. Note: For seasonal data, it’s desirable for p and h to be integer multiples of the number of obsevations in a year. e.g. For quarterly data, h = 8 and p = 4 are recommended. cycle : array of cyclical component trend : trend component