rrar(VGAM)
rrar()所属R语言包：VGAM
Nested reduced-rank autoregressive models for multiple
降秩嵌套多个自回归模型
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Estimates the parameters of a nested reduced-rank autoregressive model for multiple time series.
一个嵌套的降秩为多个时间序列的自回归模型的参数估计。
用法----------Usage----------
rrar(Ranks = 1, coefstart = NULL)
参数----------Arguments----------
参数：Ranks
Vector of integers: the ranks of the model. Each value must be at least one and no more than M, where M is the number of response variables in the time series. The length of Ranks is the lag, which is often denoted by the symbol L in the literature.
矢量整数的行列的典范。每个值必须至少为1和不超过M，其中M是在时间序列中的响应变量的数目。 Ranks的长度的滞后性，这往往是文献中的符号L表示。
参数：coefstart
Optional numerical vector of initial values for the coefficients. By default, the family function chooses these automatically.
可选数值的矢量系数的初始值。默认情况下，家庭的功能会自动选择这些。
Details
详细信息----------Details----------
Full details are given in Ahn and Reinsel (1988). Convergence may be very slow, so setting maxits = 50, say, may help. If convergence is not obtained, you might like to try inputting different initial values.
详情在安贞焕和赖因泽尔（1988）。收敛速度可能会很慢，所以设置maxits = 50，说，可以帮助。如果不收敛，你可能想尝试输入不同的初始值。
Setting trace = TRUE in vglm is useful for monitoring the progress at each iteration.
设置trace = TRUEvglm是用于监测在每次迭代的进度。
值----------Value----------
An object of class "vglmff" (see vglmff-class). The object is used by modelling functions such as vglm and vgam.
类的一个对象"vglmff"（见vglmff-class）。该对象被用于建模功能如vglm和vgam。
注意----------Note----------
This family function should be used within vglm and not with rrvglm because it does not fit into the RR-VGLM framework exactly. Instead, the reduced-rank model is formulated as a VGLM!
家庭功能，应使用内vglm，而不是用rrvglm，因为它完全不适合到RR-VGLM的框架。相反，降秩模型配制作为VGLM！
A methods function Coef.rrar, say, has yet to be written. It would return the quantities Ak1, C, D, omegahat, Phi, etc. as slots, and then show.Coef.rrar would also need to be written.
一个方法能够Coef.rrar，说，至今还没有被写入。这将返回的数量Ak1，C，D，omegahat，Phi“等，槽，然后show.Coef.rrar也需要以被写入。
（作者）----------Author(s)----------
T. W. Yee
参考文献----------References----------
Nested reduced-rank autoregressive models for multiple time series. Journal of the American Statistical Association, 83, 849–856.
参见----------See Also----------
vglm, grain.us.
vglm，grain.us。
实例----------Examples----------
year = seq(1961 + 1/12, 1972 + 10/12, by = 1/12)
## Not run: par(mar = c(4, 4, 2, 2) + 0.1, mfrow = c(2, 2))[＃不运行：PAR（MAR = C（4，4，2，2）+ 0.1，mfrow = C（2，2））]
for(ii in 1:4) {
plot(year, grain.us[, ii], main = names(grain.us)[ii], las = 1,
type = "l", xlab = "", ylab = "", col = "blue")
points(year, grain.us[,ii], pch = "*", col = "blue")
}
## End(Not run)[＃（不执行）]
apply(grain.us, 2, mean) # mu vector[亩矢量]
cgrain = scale(grain.us, scale = FALSE) # Center the time series only[中心系列]
fit = vglm(cgrain ~ 1, rrar(Ranks = c(4, 1)), trace = TRUE)
summary(fit)
print(fit@misc$Ak1, dig = 2)
print(fit@misc$Cmatrices, dig = 3)
print(fit@misc$Dmatrices, dig = 3)
print(fit@misc$omegahat, dig = 3)
print(fit@misc$Phimatrices, dig = 2)
## Not run: par(mar = c(4, 4, 2, 2) + 0.1, mfrow = c(4, 1))[＃不运行：PAR（MAR = C（4，4，2，2）+ 0.1，mfrow = C（4，1））]
for(ii in 1:4) {
plot(year, fit@misc$Z[,ii], main = paste("Z", ii, sep = ""),
type = "l", xlab = "", ylab = "", las = 1, col = "blue")
points(year, fit@misc$Z[,ii], pch = "*", col = "blue")
}
## End(Not run)[＃（不执行）]
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注：
注1：为了方便大家学习，本文档为生物统计家园网机器人LoveR翻译而成，仅供个人R语言学习参考使用，生物统计家园保留版权。
注2：由于是机器人自动翻译，难免有不准确之处，使用时仔细对照中、英文内容进行反复理解，可以帮助R语言的学习。
注3：如遇到不准确之处，请在本贴的后面进行回帖，我们会逐渐进行修订。
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发表于 2012-10-1 15:52:00
