R 多元线性回归的预测计算

我有保险方面的资料；年龄、性别、体重指数、儿童、吸烟者、地区和费用。性别、吸烟者和地区是影响因素。性别：男，女，吸烟者：是，否，地区：东北，东南，西南，西北

m2 <- lm(charges ~ age + sex + bmi + children + smoker + region)

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我只会出错。请帮助

不要重新定义因子，只需使用

预测

中引号中的因子级别即可

predict(m2, list(age=40, sex="male", bmi=30, children=2, smoker="yes", 
                 region="northwest"), int="p", level=0.98)
#         fit       lwr      upr
# 1 -1.978994 -9.368242 5.410254

资料

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dat 1）新数据中的系数杠杆是否与旧数据中的水平匹配？在您的示例中，例如，
smoker
变量将只有一个级别（
yes
）2）尝试将新数据作为数据帧而不是列表传递。此外，传递新数据时，需要引用字符串
smoker=factor（yes）
将查找名为
yes
的对象。也许你的意思是像吸烟者=因子（'yes'，水平=c（'yes'，'no'））

。

predict(m2, list(age=40, sex=factor(male), bmi=30, children=2, smoker=factor(yes), 
                 region=factor(northwest)), int="p", level=0.98)

predict(m2, list(age=40, sex="male", bmi=30, children=2, smoker="yes", 
                 region="northwest"), int="p", level=0.98)
#         fit       lwr      upr
# 1 -1.978994 -9.368242 5.410254

dat <- structure(list(charges = c(1.37095844714667, -0.564698171396089, 
0.363128411337339, 0.63286260496104, 0.404268323140999, -0.106124516091484, 
1.51152199743894, -0.0946590384130976, 2.01842371387704, -0.062714099052421
), age = c(20L, 58L, 44L, 53L, 22L, 51L, 20L, 75L, 59L, 41L), 
    sex = structure(c(2L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), .Label = c("female", 
    "male"), class = "factor"), bmi = c(25.3024309248682, 24.6058854935878, 
    25.7881406228236, 25.6707038267505, 24.0508191903124, 25.036135738485, 
    27.115755613237, 25.1674409043556, 24.1201634714689, 25.9469131749433
    ), children = c(4L, 1L, 5L, 1L, 1L, 4L, 0L, 0L, 3L, 4L), 
    smoker = c("no", "yes", "yes", "no", "no", "yes", "yes", 
    "yes", "yes", "no"), region = structure(c(1L, 2L, 2L, 3L, 
    1L, 2L, 3L, 3L, 3L, 2L), .Label = c("northeast", "northwest", 
    "southeast"), class = "factor")), row.names = c(NA, -10L), class = "data.frame")