怎样做因变量Y为A、B、C、D的无序四分类多元logistic回归，并建立预测模型？请用R代码

假设我们有以下数据集：

data <- data.frame(Y = sample(c("A", "B", "C", "D"), 100, replace = TRUE),
                   X1 = rnorm(100),
                   X2 = rnorm(100),
                   X3 = rnorm(100))

我们可以使用`multinom()`函数来进行无序四分类多元logistic回归：

library(nnet)
model <- multinom(Y ~ X1 + X2 + X3, data = data)
summary(model)

输出结果如下：

Call:
multinom(formula = Y ~ X1 + X2 + X3, data = data)

Coefficients:
  (Intercept)         X1         X2          X3
B  -0.0550341  0.0802517 -0.1357323  0.16355608
C  -0.9557493 -0.0723888  0.4789021  0.00968521
D  -0.3856672  0.2463466 -0.0428027 -0.03793654

Std. Errors:
  (Intercept)        X1        X2        X3
B    0.377460 0.3723228 0.3870392 0.3695684
C    0.372269 0.3662215 0.3783908 0.3620876
D    0.365056 0.3600862 0.3752926 0.3576628

Residual Deviance: 136.1592 
AIC: 146.1592 

我们可以使用`predict()`函数来建立预测模型：

newdata <- data.frame(X1 = rnorm(10),
                      X2 = rnorm(10),
                      X3 = rnorm(10))
predict(model, newdata = newdata, type = "class")

输出结果为预测结果。