dregar2: Estimating adaptive/non-adaptive DREGAR coefficients using an...

In DREGAR: Regularized Estimation of Dynamic Linear Regression in the Presence of Autocorrelated Residuals (DREGAR)

Description

Estimating coefficients for penalized dynamic regression in the presence of autocorrelated residuals using an iterative 6-step procedure.

Usage

dregar6(data , da, ar, mselection = 4, type = "alasso", 
      normalize = FALSE, iteration = 15,  intercept=FALSE)

Arguments

data	Data matrix of order (time, response, covariates)
da	A vector of lags. Autoregressive orders for the response. For example 1:p for all lags from 1 to p
ar	A vector of lags. Autoregressive orders for residuals. For example 1:q for all lags from 1 to q
mselection	Model selection criteria. Choosing among 1 (CP), 2 (AIC), 3 (GCV) and 4 (BIC)
type	Type of penalty. Choosing between 'enet' and 'alasso' for DREGAR and adaptive-DREGAR penalties.
normalize	Logical flag. Setting to TRUE to normalise data prior to analysis
iteration	The number of iterations
intercept	Logical flag. Setting to TRUE to have intercept in the model.

Author(s)

Hamed Haselimashhadi <[e-mail]>

See Also

dregar2, generateAR , sim.dregar

Examples

 par(mfrow=c(2,2))
  m=sim.dregar(n=500 ,  beta=1:4, phi=generateAR(2), theta=.1, 
               n.z.coeffs=3 , plot=TRUE) # generating data
  r=dregar6(data=m$rawdata, da = 1:3,
      ar = 1:2,mselection = 4,
      type='alasso')# estimating parameters using (non-apdative) DREGAR 
  round(cbind(
    true      = c(phi=c(m$phi,0),theta=c(m$theta,0),beta=m$beta),
    estimates = c(phi=r$phi,theta=r$theta,beta=r$beta)
  )
  ,3
  )
  plot(r$mod.phi,main='phi')
  plot(r$mod.theta,main='theta')
  plot(r$mod.beta,main='beta')

Example output

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 Iteration  15  / 15         true estimates
phi1    0.732     0.736
phi2   -0.107    -0.095
phi3    0.000     0.000
theta1  0.100     0.000
theta2  0.000     0.000
beta1   1.000     0.928
beta2   2.000     2.009
beta3   3.000     3.351
beta4   4.000     3.839
beta5   0.000     0.000
beta6   0.000     0.000
beta7   0.000     0.000

DREGAR documentation built on May 2, 2019, 7:59 a.m.