无截距的总最小二乘回归，R [英] Total Least squares regression without intercept, with R

问题描述

我需要使用以下公式计算两个价格之间的回归系数beta:

I need to calculate the beta of a regression between two prices with:

1. 没有拦截
2. 使用总最小二乘估计

R中有执行功能prcomp. 之后，如何提取Beta?

In R there is the function prcomp to perform it. After it, how can I extract the beta?

代码是

`library(quantmod)
# how to get closes
getCloses <- function(sym) {
    ohlc <- getSymbols(sym, from="2009-01-01", to="2011-01-01",
                       auto.assign=FALSE, return.class="zoo")
    Cl(ohlc)}
# how to import data (2 assets)
closes <- merge(IWM=getCloses("IWM"),
            VXZ=getCloses("VXZ"), all=FALSE)
# function for hedging ratio
tlsHedgeRatio <- function(p, q) {
    r <- princomp( ~ p + q+0)
    r$loadings[1,1] / r$loadings[2,1]
}
# get the hedging ratio
with(closes, {
    cat("TLS for VXZ vs. IWM =", tlsHedgeRatio(VXZ,IWM), "\n")
})`    

在代码中显示了如何使用拦截执行TLS回归.我试图执行相同而没有拦截. 在使用lm函数的同时，添加+0允许执行回归而不截距，如何使用prcomp函数执行同样的操作?

In the code show how to perform TLS regression with intercept. I trying to perform the same without intercept. While with lm function, adding +0 allow to perform regression without intercept, how could I do the same with prcompfunction?

推荐答案

如果R是包含数据的矩阵

If R is the matrix that contains the data

pcaresult <- prcomp(R)
eigenVect <- pcaresult$rotation
eigenVal <- (pcaresult$sdev)^2
coeff1 = as.numeric(coeff$eigenvectors[,"PC2"][1])
coeff2 = -as.numeric(coeff$eigenvectors[,"PC2"][2])
ratio = coeff2/coeff1

您还可以检查功能?MethComp::Deming(位于软件包MethComp中)，其结果类似.

you can also check the function ?MethComp::Deming (in package MethComp) which gives similar result.

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