Description Usage Arguments Value References See Also Examples
Packs the parameters defining a specfied stochastic fractal time series model into a list an returns the result.
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model |
a character string defining the model type. Choices are
|
Cs |
pure power law constant.
If supplied, this argument is used to compute |
HB |
the Hurst coefficient for a DFBM process. Default: |
HG |
the Hurst coefficient for an FGN process. Default: |
M |
sets the number of terms used
in the Euler-Maclaurin summation
for calculating the SDF of an FGN process and DFBM process.
The default value should be adequate
for all values of the Hurst coefficient.
Default: |
alpha |
power law exponent for a PPL model. Default: |
bterms |
an integer used to control the number of primary terms cumulatively summed in computing an ACVS for a PPL process. Default: |
delta |
the FD parameter. Default: |
dterms |
an integer used to control the number of secondary terms cumulatively summed in computing an ACVS for a PPL process. Default: |
innovations.var |
innovations variance for an FD or PPL model.
If supplied, this argument is used to compute |
variance. |
the process variance with a default of unity.
If |
an object of class lmModel
containing a list of model parameters.
D. Percival and A. Walden (2000), Wavelet Methods for Time Series Analysis, Cambridge University Press, Chapter 7.
J. Beran (1994), Statistics for Long-Memory Processes, Chapman and Hall, Chapter 2.
D. Percival and A. Walden (1993), Spectral Analysis for Physical Applications, Cambridge University Press, 1993, Chapter 9.
lmACF
, lmSDF
, lmSimulate
, lmConvert
, lmConfidence
, FDWhittle
.
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