# rank.est: Cointegration Rank Estimation using Model Selection. In FunWithR/LongMemoryTS: Long Memory Library

## Description

Model selection procedure to estimate the cointegrating rank based on eigenvalues of correlation matrix P suggested by Robinson and Yajima (2002).

## Usage

 `1` ```rank.est(data, d.hat, m, m1, v_n = m^(-0.3)) ```

## Arguments

 `data` data matrix of dimension (qxT). `d.hat` the estimated d.vector `m` bandwith parameter specifying the number of Fourier frequencies. used for the estimation of d, usually `floor(1+T^delta)`, where 0>m `v_n` bandwidth parameter. Nielsen and Shimotsu (2007) use m^(-0.3) in their simulation studies, which s the default value. m^(-b) mit 0

## References

Robinson, P. M. and Yajima, Y. (2002): Determination of cointegrating rank in fractional systems. Journal of Econometrics, Vol. 106, No.2, pp. 217-241.

Nielsen, M. O. and Shimotsu, K. (2007): Determining the coinegrating rank in nonstationary fractional systems by the exact local Whittle approach. Journal of Econometrics, 141, pp. 574-596.

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11``` ```T<-2000 d<-0.4 m1<-floor(1+T^0.75) m<-floor(1+T^0.65) xt<-fracdiff.sim(n=T, d=d)\$series yt<-xt+rnorm(T) zt<-xt+rnorm(T) X<-cbind(xt,yt,zt) lW.wrap<-function(data,m){local.W(data,m)\$d} d.hat<-apply(X,2,lW.wrap, m=m1) rank.est(data=X, d.hat, m=m, m1=m1) ```

FunWithR/LongMemoryTS documentation built on Jan. 19, 2019, 10:42 p.m.