simple linear regression equation r studio

If I understand what you're trying to do, this will be useful: library(tidyverse) The first argument to lm should be a formula and the second should be the data. But one thing I notice is that the pipe to lm will use that data frame as the first argument to lm. Hard to be sure because I'm not familiar with your data. The second option gives the error Error in eval(predvars, data, env) : object 'x' not found , data = df, subset = indep_var ~ : invalid type (closure) for the variable 'data'. The first option gives the error Error in (formula =. I also tried lm(indep_var~.,data =df$data) since the column where all variables are nested in within df is called data but this does not work either. Lm(indep_var~.,data =df) #this is where it does not work. Then I group the dataset and nest all values per coordinate pair model% So far I grouped the dataset by x and y and nested all other variables so that each row contains one column each with x and y coordinate and one column containing a data rame with the independent and predictor variables and one variable indicating the yearįirst I load the respective dataframe 'df' as rds

I want to perform a simple linear regression for a timeseries of 30 years per gridcell (x,y coordinate pair). I have a dataframe that contains coordinates describing each one gridcell, year indications and several variables which I want to include in my linear regression.

Simple linear regression equation r studio