在lm回归中使用偏移量-R [英] Use of offset in lm regression - R

问题描述

我有这个程序

dens <- read.table('DensPiu.csv', header = FALSE)
fl <- read.table('FluxPiu.csv', header = FALSE)
mydata <- data.frame(c(dens),c(fl))

dat = subset(mydata, dens>=3.15)
colnames(dat) <- c("x", "y")
attach(dat)

我想对 dat 中包含的数据进行最小二乘回归，该函数的形式为

and I want to do a least-square regression on the data contained in dat, the function has the form

y ~ a + b*x

，我希望回归线穿过特定点P(x0，y0)(不是原点).

and I want the regression line to pass through a specific point P(x0,y0) (which is not the origin).

我正在尝试这样做

 x0 <- 3.15 

 y0 <-283.56

 regression <- lm(y ~ I(x-x0)-1, offset=y0)

(我认为在这种情况下，data = dat并不是必需的)，但是我有此错误:

(I think that data = dat is not necessary in this case) but I have this error :

Error in model.frame.default(formula = y ~ I(x - x0) - 1, : variable
 lengths differ (found for '(offset)').

我不知道为什么.我想我没有正确定义偏移量值，但在互联网上找不到任何示例.

I don't know why. I guess that I haven't defined correctly the offset value but I couldn't find any example on the internet.

有人可以向我解释偏移量的工作方式吗?

Can anybody explain me how offset works please?

推荐答案

您的偏移项必须是变量，例如x和y，而不是数字常量.因此，您需要在数据集中使用适当的值创建一列.

Your offset term has to be a variable, like x and y, not a numeric constant. So you need to create a column in your dataset with the appropriate values.

dat$o <- 283.56
lm(y ~ I(x - x0) - 1, data=dat, offset=o)

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