1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
|
\name{UnitrootDistribution}
\alias{UnitrootDistribution}
\alias{punitroot}
\alias{qunitroot}
\title{Unit Root Distribution}
\description{
A collection and description of functions to compute distribution
function and quantile function for the unit root test statistics.
\cr
The functions are:
\tabular{ll}{
\code{punitroot} \tab the cumulative probability, \cr
\code{qunitroot} \tab the quantiles of the unit root test statistics. }
}
\usage{
punitroot(q, n.sample = 0, trend = c("c", "nc", "ct", "ctt"),
statistic = c("t", "n"), na.rm = FALSE)
qunitroot(p, n.sample = 0, trend = c("c", "nc", "ct", "ctt"),
statistic = c("t", "n"), na.rm = FALSE)
}
\arguments{
\item{n.sample}{
the number of observations in the sample from which the
quantiles are to be computed. Specify \code{n.sample=0}
for asymptotic quantiles. The default is 0.
}
\item{na.rm}{
a logical value. If set to \code{TRUE}, missing values will
be removed otherwise not, the default is \code{FALSE}.
}
\item{p}{
a numeric vector of probabilities. Missing values are
allowed.
}
\item{q}{
vector of quantiles or test statistics. Missing values
are allowed.
}
\item{statistic}{
a character string describing the type of test statistic.
Valid choices are \code{"t"} for t-statistic, and \code{"n"}
for normalized statistic, sometimes referred to as the
rho-statistic. The default is \code{"t"}.
}
\item{trend}{
a character string describing the regression from which the
quantiles are to be computed. Valid choices are: \code{"nc"}
for a regression with no intercept (constant) nor time trend,
and \code{"c"} for a regression with an intercept (constant)
but no time trend, \code{"ct"} for a regression with an intercept
(constant) and a time trend. The default is \code{"c"}.
}
}
\value{
The function \code{punitroot} returns the cumulative probability
of the asymptotic or finite sample distribution of the unit root
test statistics.
The function \code{qunitroot} returns the quantiles of the
asymptotic or finite sample distribution of the unit root test
statistics, given the probabilities.
}
\note{
The program uses the Fortran routines and the tables from J.G.
McKinnon (1988). Many thanks to J.M. McKinnon putting his code
and tables under the GPL license, which made this implementation
possible.
}
\authors{
J.G. McKinnon for the underlying Fortran routine and the tables, \cr
Diethelm Wuertz for the Rmetrics \R-port.
}
\references{
Dickey, D.A., Fuller, W.A. (1979);
\emph{Distribution of the estimators for autoregressive time
series with a unit root},
Journal of the American Statistical Association 74, 427--431.
MacKinnon, J.G. (1996);
\emph{Numerical distribution functions for unit root and
cointegration tests},
Journal of Applied Econometrics 11, 601--618.
Phillips, P.C.B., Perron, P. (1988);
\emph{Testing for a unit root in time series regression},
Biometrika 75, 335--346.
}
\examples{
% The data files can only be found in the productive environment,
% since the files are zipped!
\dontrun{
## qunitroot -
# Asymptotic quantile of t-statistic
qunitroot(0.95, trend = "nc", statistic = "t")
## qunitroot -
# Finite sample quantile of n-statistic
qunitroot(0.95, n.sample = 100, trend = "nc", statistic = "n")
## punitroot -
# Asymptotic cumulative probability of t-statistic
punitroot(1.2836, trend = "nc", statistic = "t")
## punitroot -
# Finite sample cumulative probability of n-statistic
punitroot(1.2836, n.sample = 100, trend = "nc", statistic = "n")
}
}
\keyword{distribution}
|
