ldhmm.ld_stats: Computes the theoretical statistics per state
In ldhmm: Hidden Markov Model for Financial Time-Series Based on Lambda Distribution
Description
Usage
Arguments
Value
Author(s)
View source: R/ldhmm-ld_stats.R
Description
This utility computes the statistics (mean, sd, kurtosis) based on the lambda distribution.
This is used to compare to the statistics from observations for each state.
Usage
1
ldhmm.ld_stats(object, annualize = FALSE, days.pa = 252)
Arguments
object
an ldhmm object
annualize
logical, to annaulize the sd and mean to V (xsqrt(days.pa)x100) and R (xdays.pa).
Default is FALSE.
days.pa
a positive integer, specifying number of days per year, default is 252.
Value
a matrix of statistics for each state, size of states times 3
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)
View source: R/ldhmm-ld_stats.R
Description
This utility computes the statistics (mean, sd, kurtosis) based on the lambda distribution. This is used to compare to the statistics from observations for each state.
Usage
1 | ldhmm.ld_stats(object, annualize = FALSE, days.pa = 252)
|
Arguments
object |
an ldhmm object |
annualize |
logical, to annaulize the sd and mean to V (xsqrt(days.pa)x100) and R (xdays.pa).
Default is |
days.pa |
a positive integer, specifying number of days per year, default is 252. |
Value
a matrix of statistics for each state, size of states times 3
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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