如何在 R 中拟合受限 VAR 模型? [英] How to fit a restricted VAR model in R?

问题描述

我试图了解如何拟合特定且不一般.

据我所知，拟合诸如一般 VAR(1) 之类的模型是由从 Cran 导入vars"包

例如

认为 y 是一个 10 x 2 的矩阵.然后我在导入 vars 包后这样做了

y=df[,1:2] # df 是一个有很多列的数据框(只关心前两个)VARselect(y, lag.max=10, type="const")总结(fitHilda <- VAR(y，p=1，类型=const"))

如果对系数没有限制，这可以正常工作.但是，如果我想在 R 中拟合这个受限制的 VAR 模型

我如何在 R 中这样做?如果你知道，请给我一个页面?如果您有任何不清楚的地方，请不要记下，让我知道它是什么，我会尽量把它说清楚.

非常感谢您提前

解决方案

我无法找到如何按照我想要的方式设置限制.但是，我找到了一种方法来通过执行以下操作.

尝试使用特定的信息标准(如

)找出滞后的数量

VARselect(y, lag.max=10, type="const")

这将使您能够找到滞后长度.我发现它是我的情况之一.然后将 VAR(1) 模型拟合到您的数据中.在我的情况下是 y.

t=VAR(y, p=1, type="const")

当我查看摘要时.我发现某些系数在统计上可能不显着.

summary(t)

然后从包'vars'运行内置函数

t1=restrict(t, method = "ser", thresh = 2.0, resmat = NULL)

此函数通过按重要性强加零限制来实现对 VAR 的估计

看结果写

summary(t1)

I was trying to understand how may I fit a VAR model that is specific and not general.

I understand that fitting a model such as general VAR(1) is done by importing the "vars" package from Cran

for example

consider that y is a matrix of a 10 by 2. then I did this after importing vars package

y=df[,1:2] # df is a dataframe with alot of columns (just care about the first two)
VARselect(y, lag.max=10, type="const")
summary(fitHilda <- VAR(y, p=1, type="const"))

This work fine if no restriction is being made on the coefficients. However, if I would like to fit this restricted VAR model in R

How may I do so in R? Please refer me to a page if you know any? If there is anything unclear from your prespective please do not mark down let me know what is it and I will try to make it as clear as I understand.

Thank you very much in advance

解决方案

I was not able to find how may I put restrictions the way I would like to. However, I find a way to go through that by doing as follow.

Try to find the number of lags using a certain information criterion like

VARselect(y, lag.max=10, type="const")

This will enable you to find the lag length. I found it to be one in my case. Then afterwards fit a VAR(1) model to your data. which is in my case y.

t=VAR(y, p=1, type="const")

When I view the summary. I find that some of the coefficients may be statistically insignificant.

summary(t)

Then afterwards run the built-in function from the package 'vars'

t1=restrict(t, method = "ser", thresh = 2.0, resmat = NULL)

This function enables one to Estimation of a VAR, by imposing zero restrictions by significance

to see the result write

summary(t1)

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