r - 将 predict.glm 与用户定义的函数一起使用

Question

我最近安装了一个 glm 模型。我目前正在尝试更改其中一个参数(例如截距，同时保持其他参数不变)以查看它如何影响预测。我想到了两种方法，但都失败了:

手动更改 glm 模型(我做不到)或者自己编写一个函数并将其作为 glm 类

我想将我的“用户定义”模型与 predict.glm() 结合使用，看看这对预测有何影响。下面给出了一个类似于我的模型的示例:

> fit <- glm(formula = am ~ wt+cyl , family = binomial, data = mtcars)
> fit

Call:  glm(formula = am ~ wt + cyl, family = binomial, data = mtcars)

Coefficients:
(Intercept)           wt          cyl  
     15.749       -7.864        1.322  

Degrees of Freedom: 31 Total (i.e. Null);  29 Residual
Null Deviance:      43.23 
Residual Deviance: 14.73        AIC: 20.73

有没有办法手动编辑“拟合”模型并将其作为 glm 用于预测？我不是核心统计学家，所以我希望这一切都有意义。谢谢

Answer 1

您可以手动更改fit 中的系数并使用predict 函数。

# Fit the model:
fit <- glm(formula = am ~ wt+cyl , family = binomial, data = mtcars)
# Look at the first few predictions:
head(predict(fit, mtcars))


        Mazda RX4     Mazda RX4 Wag        Datsun 710    Hornet 4 Drive 
        3.0761275         1.0708076         2.7918672        -1.6029523 
Hornet Sportabout           Valiant 
       -0.7288921        -3.5296322 

# Change the intercept to 10 for example:
fit$coefficients[1] <- 10

# Look at the first few predictions again (notice they are different):
print(head(predict(fit, mtcars)))

head(predict(fit, mtcars))
    Mazda RX4     Mazda RX4 Wag        Datsun 710    Hornet 4 Drive 
    -2.673299         -4.678619         -2.957559         -7.352378 
Hornet Sportabout           Valiant 
        -6.478318         -9.279058