GetFitHRegL1: Compute loglikelihood ratio test statistic under the laplace...
In ptest: Periodicity Tests in Short Time Series
Description
Usage
Arguments
Details
Value
Author(s)
References
Description
The -2 loglikelihood ratio test statistic, -2LLR, is computed
for testing for periodicity under the laplace noises.
Usage
1
GetFitHRegL1(y)
Arguments
y
Vector containing the series.
Details
To compute the likelihood ratio statistic,
a harmonic regression model is fitted by
the maximum likelihood estimations (MLE)
according to the selected model. In particular, the frequency f is found by
the grid search among
En = {j/101 | j=1,…,50 and j/101 ≥ 1/n}.
The MLE is equivalent to
the least absolute estimation.
The computation is completed by the Exterior Point Methods
with theimported function rq.fit.br
from the package quantreg.
Value
Vector of length 2 containing
the -2 loglikelihood ratio test statistic under the laplace noises
and the estimated frequency.
Author(s)
Yuanhao Lai
References
Li, T. H. (2010). A nonlinear method for robust spectral analysis.
Signal Processing, IEEE Transactions on, 58(5), 2466-2474.
ptest documentation built on May 2, 2019, 5:58 a.m.
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Description Usage Arguments Details Value Author(s) References
Description
The -2 loglikelihood ratio test statistic, -2LLR, is computed for testing for periodicity under the laplace noises.
Usage
1 | GetFitHRegL1(y)
|
Arguments
y |
Vector containing the series. |
Details
To compute the likelihood ratio statistic,
a harmonic regression model is fitted by
the maximum likelihood estimations (MLE)
according to the selected model. In particular, the frequency f is found by
the grid search among
En = {j/101 | j=1,…,50 and j/101 ≥ 1/n}.
The MLE is equivalent to
the least absolute estimation.
The computation is completed by the Exterior Point Methods
with theimported function rq.fit.br
from the package quantreg.
Value
Vector of length 2 containing the -2 loglikelihood ratio test statistic under the laplace noises and the estimated frequency.
Author(s)
Yuanhao Lai
References
Li, T. H. (2010). A nonlinear method for robust spectral analysis. Signal Processing, IEEE Transactions on, 58(5), 2466-2474.
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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