Time Series Analysis
- FOURIER — Fourier or inverse Fourier transform
- HPFILTER — Hodrick Prescott Filter
- INTERPOLATION — interpolated values corresponding to the given abscissa targets
- PERIODOGRAM — periodogram of the given data
FOURIER
Synopsis
FOURIER(Sequence,Inverse,Separate)
Arguments
Sequence: the data sequence to be transformed
Inverse: if true, the inverse Fourier transform is calculated, defaults to false
Separate: if true, the real and imaginary parts are given separately, defaults to false
Description
This array function returns the Fourier or inverse Fourier transform of the given data sequence.
The output consists of one column of complex numbers if Separate is false and of two columns of real numbers if Separate is true.
If Separate is true the first output column contains the real parts and the second column the imaginary parts.
Note
If Sequence is neither an n by 1 nor 1 by n array, this function returns #VALUE!
HPFILTER
Synopsis
HPFILTER(Sequence,λ)
Arguments
Sequence: the data sequence to be transformed
λ: filter parameter λ, defaults to 1600
Description
This array function returns the trend and cyclical components obtained by applying the Hodrick Prescott Filter with parameter λ to the given data sequence.
The output consists of two columns of numbers, the first containing the trend component, the second the cyclical component.
Note
If Sequence is neither an n by 1 nor 1 by n array, this function returns #VALUE! If Sequence contains less than 6 numerical values, this function returns #VALUE!
INTERPOLATION
Synopsis
INTERPOLATION(abscissae,ordinates,targets,interpolation)
Arguments
abscissae: abscissae of the given data points
ordinates: ordinates of the given data points
targets: abscissae of the interpolated data
interpolation: method of interpolation, defaults to 0 ('linear')
Description
The output consists always of one column of numbers.
Possible interpolation methods are:
0: linear;
1: linear with averaging;
2: staircase;
3: staircase with averaging;
4: natural cubic spline;
5: natural cubic spline with averaging.
Note
The abscissae should be given in increasing order. If the abscissae is not in increasing order the INTERPOLATION function is significantly slower. If any two abscissae values are equal an error is returned. If any of interpolation methods 1 ('linear with averaging'), 3 ('staircase with averaging'), and 5 ('natural cubic spline with averaging') is used, the number of returned values is one less than the number of targets and the target values must be given in increasing order. The values returned are the average heights of the interpolation function on the intervals determined by consecutive target values. Strings and empty cells in abscissae and ordinates are ignored. If several target data are provided they must be in the same column in consecutive cells.
See also
PERIODOGRAM
Synopsis
PERIODOGRAM(ordinates,filter,abscissae,interpolation,number)
Arguments
ordinates: ordinates of the given data
filter: windowing function to be used, defaults to no filter
abscissae: abscissae of the given data, defaults to regularly spaced abscissae
interpolation: method of interpolation, defaults to none
number: number of interpolated data points
Description
If an interpolation method is used, the number of returned values is one less than the number of targets and the targets values must be given in increasing order.
The output consists always of one column of numbers.
Possible interpolation methods are:
0: linear;
1: linear with averaging;
2: staircase;
3: staircase with averaging;
4: natural cubic spline;
5: natural cubic spline with averaging.
Possible window functions are:
0: no filter (rectangular window)
1: Bartlett (triangular window)
2: Hahn (cosine window)
3: Welch (parabolic window)
Note
Strings and empty cells in abscissae and ordinates are ignored. If several target data are provided they must be in the same column in consecutive cells.