R软件如何在GARCH模型中加入虚拟变量？

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在GARCH模型中加入一个虚拟变量应该如何通过编程实现呢？就是w如何编到程序里呢？？

rm(list=ls(all=T))

library(rugarch)

r=read.table("F: /数据/1.txt")

w=read.table("F: /数据/3.txt")

spec = ugarchspec(variance.model =list(model = "sGARCH", garchOrder = c(1, 1),

submodel =NULL, external.regressors =w,variance.targeting = TRUE),

mean.model = list(armaOrder = c(1, 1),include.mean = TRUE, archm = FALSE,

archpow = 1, arfima = FALSE,external.regressors = NULL, archex = FALSE),

distribution.model = "norm")

fit = ugarchfit(data = r, spec = spec)

fit

我自己写的程序的运行结果一直报错：

警告信息：1: In mean.default(newX[, i], ...) :  argument is not numeric or logical: returning NA2: In .solnpsolver(pars, fun, Ifn, ILB, IUB, control, LB, UB, ...) : rgarch-->warning: no convergence...
3: In .sgarchfit(spec = spec, data = data, out.sample = out.sample,  : ugarchfit-->warning: solver failer to converge.> fit
*---------------------------------**          GARCH Model Fit        **---------------------------------*
Conditional Variance Dynamics   -----------------------------------GARCH Model     : sGARCH(1,1)Mean Model      : ARFIMA(1,0,1)Distribution    : norm
Convergence Problem:Solver Message: Error in fun(pars, ...) : (串列)对象不能强制改变成'double'种类 求大神指教啊啊啊啊！！！！！！！！！！！！！！1

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关键词：GARCH模型 ARCH模型 GARCH 虚拟变量 ARCH 模型 软件 如何

同求

给你举个例子吧，感觉这个还是比较详细的

举一个例子：

#get data

re <- read.table("return.csv",sep=",",header=TRUE)

re[,1] <- as.character(re[,1])

re[,1] <- as.Date(re[,1])

#create dummy variable

re$T <- re[,1]>as.Date("2010-03-31")

re$T <- as.numeric(re$T)

T <- as.matrix(re$T)

library("xts")

xts <- as.xts(re[,-1],order.by=re[,1])

library("rugarch")

#GARCH specification

garchspec <- ugarchspec(variance.model = list(model = "sGARCH", garchOrder = c(1, 1),

                        submodel = NULL, external.regressors = T,

                        variance.targeting = FALSE),

                        mean.model = list(armaOrder = c(0, 0), include.mean = TRUE,

                        archm = TRUE, archpow = 1, arfima = FALSE,

                        external.regressors = NULL, archex = FALSE),

                        distribution.model = "ged",

                        start.pars = list(), fixed.pars = list())

#fitting

fit <- ugarchfit(spec=garchspec, data=xts[,1], out.sample = 0,solver="solnp",

                 solver.control = list(trace=0), fit.control =

                 list(stationarity = 1, fixed.se = 0, scale = 0, rec.init = 0.7))

show(fit)