R 多元线性回归：用户定义函数中的错误

我已经为MLR编写了我的函数。然而，输出似乎存在问题（参见最后的示例）

但是当我逐行运行代码时，输出是正确的

mlr <- function(dependentvar, dataset) {

x <- model.matrix(dependentvar ~., dataset) # Design Matrix for x

y <- dependentvar # dependent variable

betas <- solve(crossprod(x))%*%crossprod(x,y) # beta values

SST <- t(y)%*%y - (sum(y)^2/dim(dataset)[1]) # total sum of squares

SSres <- t(y)%*%y -(t(betas)%*%crossprod(x,y))  # sum of squares of residuals

SSreg <- SST - SSres  # regression sum of squares

sigmasqr <- SSres/(length(y) - dim(dataset)[2])  # variance or (MSE)

varofbeta <- sigmasqr[1]*solve( crossprod(x)) # variance of beta

cat("SST:", SST,"SSresiduals:", SSres,"SSregression:", SSreg, sep = "\n", append = FALSE)

return(betas)

}

即使我摆脱了

$

Height <- trees$Height
mlr(Height, trees)

高度使用以下各项：

x <- model.matrix(reformulate(".", dependentvar), dataset)
y <- dataset[[dependentvar]]

x <- model.matrix(reformulate(".", dependentvar), dataset)
y <- dataset[[dependentvar]]

mlr("Height", trees)