R 中变量的拟合值

发布于 2025-01-11 05:40:14 字数 652 浏览 0 评论 0原文

我想查看变量的拟合值，同时仍然考虑模型中的所有其他变量。我将这些描述为部分/边缘拟合值。我下面有一个玩具示例。该数据集内置于 R 中。这可能吗？

Seatbelts <- data.frame(Seatbelts)
head(Seatbelts)

Seatbelts<-Seatbelts[complete.cases(Seatbelts),]

## 75% of the sample size
smp_size <- floor(0.75 * nrow(Seatbelts))

## set the seed to make your partition reproducible
set.seed(123)
train_ind <- sample(seq_len(nrow(Seatbelts)), size = smp_size)

train <- Seatbelts[train_ind, ]
test <- Seatbelts[-train_ind, ]

# glm()
m1 <- glm(DriversKilled  ~  front + rear + kms + PetrolPrice + VanKilled + law,
          family=poisson(link = "log"),
          data=train)
fitted(m1)

原文

I want to see the fitted values by variable while still taking into account all other variables in the model. I would describe these as partial/marginal fitted values. I have a toy example below. This dataset is built into R. Is this possible?

Seatbelts <- data.frame(Seatbelts)
head(Seatbelts)

Seatbelts<-Seatbelts[complete.cases(Seatbelts),]

## 75% of the sample size
smp_size <- floor(0.75 * nrow(Seatbelts))

## set the seed to make your partition reproducible
set.seed(123)
train_ind <- sample(seq_len(nrow(Seatbelts)), size = smp_size)

train <- Seatbelts[train_ind, ]
test <- Seatbelts[-train_ind, ]

# glm()
m1 <- glm(DriversKilled  ~  front + rear + kms + PetrolPrice + VanKilled + law,
          family=poisson(link = "log"),
          data=train)
fitted(m1)

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|煩躁 2025-01-18 05:40:14

我不确定，但我认为您正在寻找效果图（或相应的数据）。

library(effects)
plot(allEffects(m1))

要获取特定值，您可以使用（例如）as.data.frame(allEffects(m1))（它返回数据的列表框架，每个框架一个预测变量）。

emmeans 包具有类似/重叠的功能。

I'm not sure, but I think you're looking for an effects plot (or the corresponding data).

library(effects)
plot(allEffects(m1))

To get the specific values, you could use (e.g.)as.data.frame(allEffects(m1)) (which returns a list of data frames, one for each predictor variable).

The emmeans package has similar/overlapping functionality.

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抱着落日 2025-01-18 05:40:14

在这里，您可以获取数据框中具有 glm 模型拟合值的变量值：

data.frame(front = train$front, rear = train$rear, kms = train$kms, 
           PetrolPrice = train$PetrolPrice, VanKilled = train$VanKilled, 
           law = train$law, Fitted = fitted(m1))

Here you get the values of the variables with the fitted value of the glm model in a dataframe:

data.frame(front = train$front, rear = train$rear, kms = train$kms, 
           PetrolPrice = train$PetrolPrice, VanKilled = train$VanKilled, 
           law = train$law, Fitted = fitted(m1))

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