pex_acf: Power-exponential autocorrelation function.
In SuperGauss: Superfast Likelihood Inference for Stationary Gaussian Time Series
pex_acf R Documentation
Power-exponential autocorrelation function.
Description
Power-exponential autocorrelation function.
Usage
pex_acf(tseq, lambda, rho)
Arguments
tseq
Vector of N time points at which the autocorrelation is to be calculated.
lambda
Timescale parameter.
rho
Power parameter.
Details
The power-exponential autocorrelation function is given by:
acf(t) = exp (-(t / λ)^ρ).
Value
An autocorrelation vector of length N.
Examples
pex_acf(tseq = 1:10, lambda = 1, rho = 2)
SuperGauss documentation built on March 18, 2022, 6:35 p.m.
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.
| pex_acf | R Documentation |
Power-exponential autocorrelation function.
Description
Power-exponential autocorrelation function.
Usage
pex_acf(tseq, lambda, rho)
Arguments
tseq |
Vector of |
lambda |
Timescale parameter. |
rho |
Power parameter. |
Details
The power-exponential autocorrelation function is given by:
acf(t) = exp (-(t / λ)^ρ).
Value
An autocorrelation vector of length N.
Examples
pex_acf(tseq = 1:10, lambda = 1, rho = 2)
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.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.