mleHK: Maximum likelihood estimation for the HKp parameters.

In HKprocess: Hurst-Kolmogorov Process

Maximum likelihood estimation for the HKp parameters.

Description

The function mleHK is used to estimate the μ, σ and H parameters of the HKp. The method for their estimation is described in eqs.8-9 (Tyralis and Koutsoyiannis 2011).

Usage

mleHK(data, interval = c(0.0001, 0.9999), tol = .Machine$double.eps^0.25)

Arguments

data	time series data
interval	H interval estimation
tol	estimation error tolerance

Value

Vector of maximum likelihood estimates of μ, σ and H.

Note

The function likelihoodfunction.c is called from the C library of the package. Ideas for creating this function came from McLeod et al. (2007).

Author(s)

Hristos Tyralis

References

McLeod AI, Yu H, Krougly ZL (2007) Algorithms for linear time series analysis: With R package. Journal of Statistical Software 23(5):1–26. doi: 10.18637/jss.v023.i05.

Tyralis H, Koutsoyiannis D (2011) Simultaneous estimation of the parameters of the Hurst-Kolmogorov stochastic process. Stochastic Environmental Research & Risk Assessment 25(1):21–33. doi: 10.1007/s00477-010-0408-x.

Examples

# Estimate the parameters for the Nile time series.

mleHK(Nile)

HKprocess documentation built on Oct. 27, 2022, 1:06 a.m.