ablrtest(urca)
ablrtest()所属R语言包:urca
Likelihood ratio test for restrictions on alpha and beta
α和β的限制似然比检验
译者:生物统计家园网 机器人LoveR
描述----------Description----------
This function estimates a restricted VAR, where the restrictions are based upon \bold{α}, i.e. the loading vectors and \bold{β}, i.e the matrix of cointegration vectors. The test statistic is distributed as χ^2 with (p-m)r + (p-s)r degrees of freedom, with m equal to the columns of the restricting matrix \bold{A}, s equal to the columns of the restricting matrix \bold{H} and p the order of the VAR.
此功能估计受限制的VAR,这里的限制是基于\bold{α},即负载向量和\bold{β},即协整向量矩阵。的检验统计量的分布作为χ^2与(p-m)r + (p-s)r自由度,m等于限制矩阵\bold{A},s等于列的列的限制矩阵\bold{H}和p的VAR的顺序。
用法----------Usage----------
ablrtest(z, H, A, r)
参数----------Arguments----------
参数:z
An object of class ca.jo.
对象的类ca.jo。
参数:H
The (p \times s) matrix containing the restrictions on \bold{β}.
(p \times s)基质中含有的限制\bold{β}。
参数:A
The (p \times m) matrix containing the restrictions on \bold{α}.
(p \times m)基质中含有的限制\bold{α}。
参数:r
The count of cointegrating relationships; <br> inferred from summary(ca.jo-object).
计数的协整关系;参考推断summary(ca.jo-object)。
Details
详细信息----------Details----------
The restricted \bold{α} matrix, as well as \bold{β} is normalised with respect to the first variable.
受限制的\bold{α}矩阵,以及\bold{β}被归一相对于第一可变。
值----------Value----------
An object of class cajo.test.
对象的类cajo.test。
(作者)----------Author(s)----------
Bernhard Pfaff
参考文献----------References----------
Inference on Cointegration – with Applications to the Demand for Money, Oxford Bulletin of Economics and Statistics, 52, 2, 169–210.
Cointegration Vectors in Gaussian Vector Autoregressive Models, Econometrica, Vol. 59, No. 6, 1551–1580.
参见----------See Also----------
ca.jo, alrtest, blrtest, cajo.test-class, ca.jo-class and urca-class.
ca.jo,alrtest,blrtest,cajo.test-class,ca.jo-class和urca-class。
实例----------Examples----------
data(denmark)
sjd <- denmark[, c("LRM", "LRY", "IBO", "IDE")]
sjd.vecm <- ca.jo(sjd, ecdet = "const", type="eigen", K=2, spec="longrun",
season=4)
HD1 <- matrix(c(1, -1, 0, 0, 0, 0, 0, 1, -1, 0, 0, 0, 0, 0, 1), c(5,3))
DA <- matrix(c(1,0,0,0, 0, 1, 0, 0, 0, 0, 0, 1), c(4,3))
summary(ablrtest(sjd.vecm, H=HD1, A=DA, r=1))
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注:
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