Hi,
While doing the ADF test in R using the following command I am getting the
error and the result..">
x.ct=ur.df(rev$REVENUE,start=1,end=length(rev$REVENUE),frequency=1)
Error in ur.df(rev$REVENUE, start = 1, end = length(rev$REVENUE), frequency
= 1) :
unused argument(s) (start = 1, end = 4, frequency = 1)
>
rev$REVENUE.ct=ur.df(rev$REVENUE,start=1,end=length(rev$REVENUE),frequency=1)
Error in ur.df(rev$REVENUE, start = 1, end = length(rev$REVENUE), frequency
= 1) :
unused argument(s) (start = 1, end = 4, frequency = 1)
> plot(rev$REVENUE.ct)
Error in plot.window(...) : need finite 'xlim' values
In addition: Warning messages:
1: In min(x) : no non-missing arguments to min; returning Inf
2: In max(x) : no non-missing arguments to max; returning -Inf
3: In min(x) : no non-missing arguments to min; returning Inf
4: In max(x) : no non-missing arguments to max; returning -Inf
> library(tseries)
> adf.test(REVENUE,alternative="explosive",k=0)
Error in NCOL(x) : object 'REVENUE' not found
> adf.test(rev$REVENUE,alternative="explosive",k=0)
Error in if (interpol == min(tablep)) warning("p-value smaller than printed
p-value") else warning("p-value greater than printed p-value") :
missing value where TRUE/FALSE needed
> summary(ur.df(rev$REVENUE,lags=0,type="trend")
+ )
###############################################
# Augmented Dickey-Fuller Test Unit Root Test #
###############################################
Test regression trend
Call:
lm(formula = z.diff ~ z.lag.1 + 1 + tt)
Residuals:
ALL 3 residuals are 0: no residual degrees of freedom!
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 171.522 NA NA NA
z.lag.1 -5.579 NA NA NA
tt 3.459 NA NA NA
Residual standard error: NaN on 0 degrees of freedom
Multiple R-squared: 1, Adjusted R-squared: NaN
F-statistic: NaN on 2 and 0 DF, p-value: NA
Value of test-statistic is: NaN NaN NaN
Critical values for test statistics:
1pct 5pct 10pct
tau3 -4.38 -3.60 -3.24
phi2 8.21 5.68 4.67
phi3 10.61 7.24 5.91
"
Can anyone tell me what is wrong with the codes???The code used is given
below.
Thanx
t=1:length(x)
plot(t,x)
trend = lm(x~t)
abline(lm(x~t))
summary(trend)
library(urca)
x = ts(x, start=1, end = length(x), frequency=1)
x.ct = ur.df(x,lags=0,type='trend')
plot(x.ct)
library(tseries)
adf.test(x,alternative = "explosive" , k=0)
summary(ur.df(x,lags=0,type='trend')
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