【发布时间】:2021-01-14 21:21:07
【问题描述】:
setwd("C:/Users/sevvalayse.yurtekin/Desktop/hw3")
data = read.table('DSE501_fall2020_HW3.csv', header= T, sep=',')
attach
data
getOption("max.print")
rs<-rowSums(data[,2:76], na.rm = TRUE)
data<-cbind(data,rs)
data
p1<-ggplot()+
geom_line(aes(y = rs, x=year), data=data)+
scale_x_continuous(breaks = seq(2004,2019,2))
p1
model = lm(rs ~ year )
model
summary(model)
residuals(model)
predict(model)
#model.fit = lm(year~rs)
#summary(model.fit)
new.year<-data.frame(
year = c(2021,2022,2023)
)
predict(model, newdata = new.year, interval = 'confidence')
data2 = read.table('TUIK_nufus_2019.csv', header = T, sep=",")
data2
total = data2$Total
mydata<-data[-c(1,2,3),]
model2 = lm(mydata~total)
model2
您好,关于 model.frame.default(formula = mydata ~ total, drop.unused.levels = TRUE) 中的错误:变量“mydata”的类型(列表)无效。
我该如何解决?我想从 2 个数据中进行回归分析。
【问题讨论】:
标签: r error-handling regression linear-regression predict