getVARmodel(RMAWGEN)
getVARmodel()所属R语言包:RMAWGEN
Either creates an VAR model or chooses a VAR model by using VAR or VARselect commands of vars package
无论是创建一个VAR模型,使用瓦尔包的VAR或VARselect命令或选择一个VAR模型
译者:生物统计家园网 机器人LoveR
描述----------Description----------
Either creates an VAR model or chooses a VAR model by using VAR or VARselect commands of vars package
无论是创建一个VAR模型,使用vars包的VAR或VARselect命令或选择一个VAR模型
用法----------Usage----------
getVARmodel(data, suffix = c("_Tx", "_Tn"), sep = "",
p = 1, type = "none", season = NULL, exogen = NULL,
lag.max = NULL, ic = "AIC", activateVARselect = FALSE,
na.rm = TRUE, n_GPCA_iteration = 0,
n_GPCA_iteration_residuals = n_GPCA_iteration,
extremes = TRUE)
参数----------Arguments----------
参数:data
see VAR and addsuffixes
看到VAR和addsuffixes
参数:suffix
see addsuffixes
看到addsuffixes
参数:sep
separator element for
分离元素
参数:p
lag considered for the auto-regression see VAR
落后考虑自回归VAR
参数:type
see VAR
看到VAR
参数:season
see VAR
看到VAR
参数:exogen
see VAR
看到VAR
参数:lag.max
see VARselect
看到VARselect
参数:ic
see VAR
看到VAR
参数:activateVARselect
logical variables. If TRUE, the function VARselect is run. Default and recommend use is FALSE.
逻辑变量。如果TRUE“的功能VARselect运行。默认情况下,建议使用FALSE。
参数:na.rm
logical variables. If TRUE (default), it takes into account NA values
逻辑变量。如果TRUE(默认),考虑到NA值
参数:n_GPCA_iteration
number of iteration of Gaussianization process for data. Defauli is 0 (no Gaussianization)
Gauss化数据过程的迭代数。 Defauli为0(无高斯化)
参数:n_GPCA_iteration_residuals
number of iteration of Gaussianization process for data. Defauli is 0 (no Gaussianization)
Gauss化的数据的过程的迭代数。 Defauli为0(无高斯化)
参数:extremes
see normalizeGaussian_severalstations and GPCA
看到normalizeGaussian_severalstations和GPCA
值----------Value----------
a varest2 or GPCAvarest2 object representing a VAR model or a GPCA-varest object which also contains the GPCA transformation parameters
一个varest2或GPCAvarest2对象,表示一个VAR模型或GPCA-varest对象的其中还包含了GPCA转换参数
注意----------Note----------
It inherits input parameters of VAR, VARselect and addsuffixes. The variable data contains the measured data on which the vector auto-regressive models is estimated. It is a matrix where each row is a realization of the vector random variable. In some application of this package, the random variables may be the daily maximum and minimum temperature anomalies for different stations. Often the the columns of data are called with the IDs of the stations whithout specifying the type of variable (e.g. minimun or maximum temperature anomalies). This means that two or more columns may have the same name. Therefore the function addsuffixes, which is called from this function, adds suitable suffixes to the column names.
继承输入参数VAR,VARselect和addsuffixes。变量data包含测量数据的向量自回归模型的估计。这是一个矩阵,其中的每一行是一个随机变量的向量实现。在某些应用中这个包,随机变量可能是不同的站日最高和最低温度异常。通常情况下,各列的data被称为与站的ID的内部消除指定的变量的类型(例如减到最少或最大温度异常)。这意味着,两个或多个列可以具有相同的名称。因此,函数addsuffixes,这是从该函数调用,将适合的列名的后缀。
summary(var)
摘要(VAR)
(作者)----------Author(s)----------
Emanuele Cordano, Emanuele Eccel
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注:
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