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Last data update: 2014.03.03

R: MLE estimation for FGN

FitFGN

R Documentation

MLE estimation for FGN

Description

Exact MLE estimation for FGN

Usage

FitFGN(z, demean = TRUE, MeanMLEQ = FALSE, lag.max = "default")

Arguments

`z`	time series, vector or ts object.
`demean`	if True, subtract mean. Otherwise assume it is zero.
`MeanMLEQ`	if True, an iterative algorithm is used for exact simultaneous MLE estimation of the mean and other parameters.
`lag.max`	the residual autocorrelations are tabulated for lags 1, ..., lag.max. Also lag.max is used for the Ljung-Box portmanteau test.

Details

The exact loglikelihood function is maximized numerically using optimize. The standard error for the H parameter is estimated (McLeod, Yu and Krougly, 2007).

Value

A list with class name "FitAR" and components:

`loglikelihood`	value of the loglikelihood
`H`	estimate of H parameter
`SEH`	SE of H estimate
`sigsqHat`	innovation variance estimate
`muHat`	estimate of the mean
`SEmu`	SE of mean
`Rsq`	R-squared, coefficient of forecastability
`LjungBox`	table of Ljung-Box portmanteau test statistics
`res`	normalized residuals, same length as z
`demean`	TRUE if mean estimated otherwise assumed zero
`IterationCount`	number of iterations in mean mle estimation
`MLEMeanQ`	TRUE if mle for mean algorithm used
`tsp`	tsp(z)
`call`	result from match.call() showing how the function was called
`DataTitle`	returns attr(z,"title")

Author(s)

A.I. McLeod

References

McLeod, A.I., Yu, Hao, Krougly, Zinovi L. (2007). Algorithms for Linear Time Series Analysis, Journal of Statistical Software.

Examples

data(NileMin)
out<-FitFGN(NileMin)
summary(out)
plot(out)
coef(out)

Results


R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(FGN)
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/FGN/FitFGN.Rd_%03d_medium.png", width=480, height=480)
> ### Name: FitFGN
> ### Title: MLE estimation for FGN
> ### Aliases: FitFGN
> ### Keywords: ts
> 
> ### ** Examples
> 
> data(NileMin)
> out<-FitFGN(NileMin)
> summary(out)
#Nile River minima series
H = 0.831,  R-sq = 38.46%
length of series = 663 ,  number of parameters = 2
mean =  11.4812518853695 RMSE =  0.696191503559154
loglikelihood = 236.52 ,  AIC = -469 ,  BIC =  -460
100 98.73 0.4887911
> plot(out)
> coef(out)
          MLE         sd Z-ratio
H   0.8314766 0.02662516  12.450
mu 11.4812519 0.29693674  38.666
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>