version 0.1.2

DESCRIPTION

@@ -1,17 +1,17 @@
 Package: nardl
 Type: Package
 Title: Nonlinear Cointegrating Autoregressive Distributed Lag Model
-Version: 0.1.1
+Version: 0.1.2
 Author: Taha Zaghdoudi
 Maintainer: Taha Zaghdoudi <zedtaha@gmail.com>
 Description: Computes the nonlinear cointegrating autoregressive distributed lag model with p lags of the dependent variables and q lags of independent variables proposed by (Shin, Yu & Greenwood-Nimmo, 2014 <doi:10.1007/978-1-4899-8008-3_9>).
 License: GPL-3
 Encoding: UTF-8
 LazyData: true
-RoxygenNote: 5.0.1
+RoxygenNote: 6.0.1
 Imports: stats, methods, car, strucchange, tseries, lmtest, matlab,
-        qpcR, Formula
+        Formula
 NeedsCompilation: no
-Packaged: 2018-01-25 14:50:50 UTC; Asus
+Packaged: 2018-02-06 21:14:33 UTC; Asus
 Repository: CRAN
-Date/Publication: 2018-01-25 14:57:20 UTC
+Date/Publication: 2018-02-06 21:20:15 UTC

MD5

@@ -1,9 +1,11 @@
-3afb4e83abd5c80a613313251132d223 *DESCRIPTION
-fe5b8572e04da4e55e2a9d9df02cc596 *NAMESPACE
+2c69fe347cd3053a6b7d86bca7f9f3a4 *DESCRIPTION
+08a4f7ad70b8402391e9752ada5c1c50 *NAMESPACE
 a542e51873be0d571257f2a1ae3b6392 *R/boundstest.R
-bdbbb2612552e5905e49396ddadcf527 *R/nardl.R
+6287375fbd4b4702de78d72b44fdb8de *R/dynmplier.R
+95c066f550272fc9ead141b7cdfa2613 *R/nardl.R
 24ac6af7df6fc51a6d99fd56ae211f9e *data/fod.rda
-50e218f11e587ea051f5d57cbf5262b3 *man/Nardl-package.Rd
-8f2959858f1eb6c82be0272d5a10dd50 *man/fod.Rd
-8893631ade3e2c057de71f848bb7cbe6 *man/nardl.Rd
-b29ed5d13fc62c5443decc406d7ee371 *man/summary.nardl.Rd
+06471780c719f63c1f35be020cf073f4 *man/Nardl-package.Rd
+c19c63e806b59f5e85ccb3da6c4304d7 *man/fod.Rd
+706457849f766b5c8bb69aebfa398880 *man/nardl.Rd
+e3ea5b8cf02555b40b471d12593c0d9d *man/plotmplier.Rd
+86199bdd050825292351ac3c77630bcc *man/summary.nardl.Rd

NAMESPACE

@@ -2,9 +2,9 @@
 
 S3method(summary,nardl)
 export(nardl)
+export(plotmplier)
 import(Formula)
 import(matlab)
-import(qpcR)
 importFrom(car,linearHypothesis)
 importFrom(graphics,abline)
 importFrom(graphics,legend)
@@ -15,6 +15,7 @@ importFrom(lmtest,bgtest)
 importFrom(stats,AIC)
 importFrom(stats,BIC)
 importFrom(stats,as.formula)
+importFrom(stats,coef)
 importFrom(stats,embed)
 importFrom(stats,lm)
 importFrom(stats,model.frame)

R/dynmplier.R

@@ -0,0 +1,100 @@
+
+mplier<-function(alpha,beta,varphi,vpi,l,h,k){
+  # k number of independent variables
+  # h is the horizon over which multipliers will be computed
+  # l max(p,q)
+  vphi<-matlab::zeros(1,l)
+  vphi[1] = 1 + alpha + varphi[1]
+  i=2
+  while(i<=l){
+    vphi[i] = varphi[i] - varphi[i-1]
+   i=i+1
+  }
+
+  vphi[l] = -varphi[l-1]
+
+  mtheta = matlab::zeros(l+1,k)
+  mtheta[1,] = vpi[1]
+  mtheta[2:3,] = vpi[2] - vpi[1] + beta
+  i=3
+  while(i<=l+1){
+    mtheta[i,] = vpi[i] - vpi[i-1]
+    i=i+1
+  }
+  mtheta[l+1,] = -vpi[l]
+  mpsi =matlab::zeros(h,k)
+  #mpsi<-NULL
+  mpsi[1,] = mtheta[1,]
+  i=1
+  while(i<=l){
+    mpsi[i+1,] = vphi[1:i]%*%mpsi[i:1,] + mtheta[i+1,]
+
+    i=i+1
+  }
+
+  i=l+1
+  mps<-vector('list',length(mpsi))
+  while(i<=h-1){
+    mps[[i+1]]<-t(vphi)%*%mpsi[i:i-l+1]
+    #mpsi<-c(mpsi[i+1],t(vphi)%*%mpsi[i-l+1:i])
+    i=i+1
+  }
+  mps<-matrix(do.call(rbind,mps)[1:h,])
+  cm<-apply(mps, 2, cumsum)
+  return(cm)
+}
+
+#'Dynamic multiplier plot
+#'
+#'@param model the fitted model
+#'@param np the selected number of lags
+#'@param k number of decomposed independent variables
+#'@param h is the horizon over which multipliers will be computed
+#'@importFrom stats lm AIC BIC as.formula model.frame model.matrix model.response na.omit sd update vcov embed resid coef
+#'@importFrom graphics abline legend lines par plot
+#'@import matlab
+#'@examples
+#'
+#' ############################
+#' # Dynamic multipliers plot
+#' ############################
+#' # Load data
+#'data(fod)
+#' reg<-nardl(food~inf,p=4,q=4,fod,ic="aic",maxlags = FALSE,graph = TRUE)
+#' plotmplier(reg,reg$np,1,10)
+#'
+#'@export
+plotmplier<-function(model,np,k,h){
+
+  if(np<=1) stop("number of lags must be > 1 ")
+  #positive
+  alpha<-as.matrix(coef(model$fit)[2:2])
+  betap<-as.matrix(coef(model$fit))[3:3]
+  betan<-as.matrix(coef(model$fit))[4:4]
+  varphi<-as.matrix(coef(model$fit)[5:(4+np)])
+  vpip<-as.matrix(coef(model$fit)[(5+np):((4+np)+np)])
+  vpin<-as.matrix(coef(model$fit)[((5+np)+np):(((4+np)+np)+np)])
+  mpp<-mplier(alpha,betap,varphi,vpip,np,h,k)
+  mpn<-mplier(alpha,betan,varphi,vpin,np,h,k)
+  x = seqa(0,1,(h+1))
+  yp<-cbind(matlab::zeros(1,1),t(mpp))
+  yn = cbind(matlab::zeros(1,1),t(mpn))
+  dmp<-mpp-mpn
+  yrange<-range(yp,yn,(yp-yn))
+  par(mar = c(5,4,4,8))
+  plot(x,yp,main="Dynamic multiplier",type = "l",ylim =yrange ,xlab ="",
+       ylab = "", col="red")
+  lines(x,yn,col="blue")
+  lines(x,(yp-yn),lty=2,col="darkgreen")
+  abline(h=0)
+  legend(par("usr")[2],par("usr")[4],
+         xpd = TRUE ,
+         bty = "n",
+   c(names(coef(model$fit)[3:3]),names(coef(model$fit)[4:4]),"Difference"),
+  lty = c(1, 1, 2),
+  cex=0.6,
+  col=c("blue","red","darkgreen"))
+
+
+
+}