使用Quadprog进行多项式回归

时间:2020-01-06 10:27:06

标签: r quadprog polynomial-approximations

我正在尝试根据示例here使用limSolve进行多项式回归。

我的代码如下。

hr <- c(9.0, 9.5, 10.0, 10.5, 11.0, 11.5, 12.0, 12.5, 13.0, 13.5, 14.0, 14.5, 15.0, 15.5, 16.0,
        16.5, 17.0, 17.5, 18.0, 18.5, 19.0, 19.5, 20.0, 20.5, 21.0, 21.5, 22.0, 22.5, 23.0, 23.5,
        24.0, 24.5, 25.0, 25.5, 26.0, 26.5, 27.0, 27.5, 28.0, 28.5, 29.0, 29.5, 30.0, 30.5, 31.0,
        31.5, 32.0, 32.5, 33.0, 33.5, 34.0, 34.5, 35.0, 35.5, 36.0, 36.5, 37.0, 37.5, 38.0, 38.5,
        39.0, 39.5)

fq <- c( 305, 310, 303, 236, 266, 241, 268, 222, 235, 230, 189, 191, 193, 162, 184, 170, 145, 147, 165,
         142, 155, 158, 130, 135, 122, 125, 126, 131, 117, 109, 112, 122, 104, 101, 76, 102, 97, 82,
         78,  78,  62,  96,  77,  73,  71,  81,  86,  85, 81, 68, 64, 73, 69, 53,  61, 66, 54,
         55,  46,  53,  48,  65)


n <- 5

# create polynomials:
for(i in 0:n) { 
  assign(paste0("poly", i), (hr^i))
}

library(Matrix)
library(limSolve)
A <- do.call(cbind, lapply( ls(patt="poly"), get) )
b <- fq
h <- rep(0,4)
B_c <- lsei(A = A, B = b, H = h, type=2)
dat$pred <- A%*%B_c$X

我收到以下错误消息:

Error in lsei(A = A, B = b, H = h, type = 2) : 
  cannot solve least squares problem - G and H not compatible

为什么会这样?我究竟做错了什么?

编辑:之所以使用limSolve而不是简单的lm,是因为我以后需要在回归上施加不等式约束。

0 个答案:

没有答案
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