ldhmm.ts_abs_acf: Computing ACF of the absolute value of a time series
In ldhmm: Hidden Markov Model for Financial Time-Series Based on Lambda Distribution
Description
Usage
Arguments
Value
Author(s)
Description
This utility computes the ACF of the absolute value of a time series as a proxy
of the auto-correlation of the volatility. It allows to drop the largest N outliers
so that they would not skew the ACF calculation.
Usage
1
ldhmm.ts_abs_acf(x, drop = 0, lag.max = 100)
Arguments
x
numeric, the observations.
drop
a positive integer, specifying number of outliers to be dropped.
lag.max
a positive integer, specifying number of lags to be computed.
Value
a vector of ACF
Author(s)
Stephen H. Lihn
ldhmm documentation built on Jan. 11, 2020, 9:16 a.m.
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Description Usage Arguments Value Author(s)
Description
This utility computes the ACF of the absolute value of a time series as a proxy of the auto-correlation of the volatility. It allows to drop the largest N outliers so that they would not skew the ACF calculation.
Usage
1 | ldhmm.ts_abs_acf(x, drop = 0, lag.max = 100)
|
Arguments
x |
numeric, the observations. |
drop |
a positive integer, specifying number of outliers to be dropped. |
lag.max |
a positive integer, specifying number of lags to be computed. |
Value
a vector of ACF
Author(s)
Stephen H. Lihn
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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