|int __stdcall NDK_BaxterKingFilter||(||double *||X,|
Computes trend and cyclical component of a macroeconomic time series using Baxter-King Fixed Length Symmetric Filter.
- status code of the operation
- Return values
NDK_SUCCESS Operation successful NDK_FAILED Operation unsuccessful. See Macros for full list.
[in,out] X is the univariate time series data (a one dimensional array). [in] N is the number of observations in X. [in] bAscending is the time order in the data series (i.e. the first data point's corresponding date (earliest date=1 (default), latest date=0)). [in] freq_min is the number of periods for the high pass filter (e.g. 6 for quarterly data, 18 for monthly data). [in] freq_max is the number of periods for the low passfilter (e.g. 32 for quarterly data, 96 for montly data). [in] K is the number of points(aka terms) to use in the approximate optimal filter. If missing, a default value of 12 is assumed [in] drift is a logical value: FALSE if no drift in time series (default), TRUE if drift in time series. [in] unitroot is a logical value: FALSE if no unit-root is in time series (default), TRUE if unit-root is in time series. [in] retTYpe is the integer enumeration for the filter output: (1= trend component (default), 2=cyclical component, 3=noise component)
- The time series is homogeneous or equally spaced.
- The time series may include missing values (NaN) at either end.
- The first and last K data points will not be filtered, hence replaced by NaN in the output time series as their values are not reliable
- The recommended values of P and Q are 6 and 32 or 40 for quarterly data, or 18 and 96 or 120 for monthly data.
- Setting Q=P produces a single band-pass filer and the cyclic component will be 0.
- The noise component is simply the original data minus the trend and cyclic component
- Proper seasonal adjustment should be carried out prior to BK filtering.
Header SFSDK.H Library SFSDK.LIB DLL SFSDK.DLL