acvs.andel8: Autocovariance and Autocorrelation Sequences for a Seasonal...
In bjw34032/waveslim: Basic Wavelet Routines for One-, Two-, and Three-Dimensional Signal Processing
acvs.andel8 R Documentation
Autocovariance and Autocorrelation Sequences for a Seasonal Persistent
Process
Description
The autocovariance and autocorrelation sequences from the time series model
in Figures 8, 9, 10, and 11 of Andel (1986). They were obtained through
numeric integration of the spectral density function.
Usage
data(acvs.andel8)
data(acvs.andel9)
data(acvs.andel10)
data(acvs.andel11)
Format
A data frame with 4096 rows and three columns: lag, autocovariance
sequence, autocorrelation sequence.
References
Andel, J. (1986) Long memory time series models,
Kypernetika, 22, No. 2, 105-123.
bjw34032/waveslim documentation built on Aug. 18, 2022, 2:36 p.m.
R Package Documentation
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| acvs.andel8 | R Documentation |
Autocovariance and Autocorrelation Sequences for a Seasonal Persistent Process
Description
The autocovariance and autocorrelation sequences from the time series model in Figures 8, 9, 10, and 11 of Andel (1986). They were obtained through numeric integration of the spectral density function.
Usage
data(acvs.andel8) data(acvs.andel9) data(acvs.andel10) data(acvs.andel11)
Format
A data frame with 4096 rows and three columns: lag, autocovariance sequence, autocorrelation sequence.
References
Andel, J. (1986) Long memory time series models, Kypernetika, 22, No. 2, 105-123.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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