r中的回归模型使用虚拟系统

发布于 2025-02-05 02:37:05 字数 722 浏览 1 评论 0原文

我想建立一个回归模型。我有有关职业毕业人，学者，非学术，女人和男人的数据。数据分开到区域（7）。我尝试键入此代码，但我不确定这是我数据的正确模型... 我很乐意为此提供帮助。

CleanData -CSV文件包含来自01/2010-04/2020的数据我删除了一个月，城市和城市名称的专栏

regressionSubset <- cleanData  
regressionSubset$MONTH <- NULL
regressionSubset$CITY <- NULL
regressionSubset$LOCALITY.NAME <- NULL

regressionData <- dummy_cols(regressionSubset, remove_first_dummy = TRUE, remove_selected_columns = TRUE)  
regressionData <- data.frame(scale(regressionData))
set.seed(42)
model <- lm(ESTIMATED.CITY.UNEMPLOYMENT ~ ., data = regressionData)
step_model <- stepAIC(model, trace = FALSE)
summary(step_model)
extract_eq(step_model, use_coefs = TRUE, wrap=TRUE, terms_per_line = 1)

原文

i want to build a regression model.
i have data about job sekeers, academics, non-academics, woman and man.
the data seperated to areas (7).
i try to type this code but im not sure that it is the right model for my data...
I would be happy to help with this.

cleanData - the csv file, contains data from 01/2010 - 04/2020
I deleted the columns of month, city and the name of the city

regressionSubset <- cleanData  
regressionSubset$MONTH <- NULL
regressionSubset$CITY <- NULL
regressionSubset$LOCALITY.NAME <- NULL

regressionData <- dummy_cols(regressionSubset, remove_first_dummy = TRUE, remove_selected_columns = TRUE)  
regressionData <- data.frame(scale(regressionData))
set.seed(42)
model <- lm(ESTIMATED.CITY.UNEMPLOYMENT ~ ., data = regressionData)
step_model <- stepAIC(model, trace = FALSE)
summary(step_model)
extract_eq(step_model, use_coefs = TRUE, wrap=TRUE, terms_per_line = 1)

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