Hi All,
How do you dynamically generate the arguments for the lm() function when
your items vary for each database.
Say in my case for a particular database i have items from i1 to i15 .
In the code below there a line like this :--
item_cat_fit<-lm(as.numeric(item_item_table$i1) ~
as.numeric(item_item_table$i2) + as.numeric(item_category_table$i3) ) *#
this gives proper results,i am accessing each column of the dataset using
column names.
*
how do i dynamically generate this :---
item_cat_fit<-lm(as.numeric(item_item_table[item_item_dependent_var_counter])
~ as.numeric(item_item_table[item_item_independent_var_counter ] ) )
*Because of this as.numeric(item_item_table[item_item_dependent_var_counter])
i get error that you cannot convert a list to double.I tried doing this
as.numeric(as.matrix(item_item_table[item_item_dependent_var_counter]))*
I also tried doing this
mode(item_item_table[item_item_dependent_var_counter])<-"numeric" but of no
use.
for(item_item_dependent_var_counter in 1:item_item_size[1]) # no of all
items
{
for(item_item_independent_var_counter in 1:(item_item_size[1] - 1))
{
item_item_third_var_data<-contrld_third_var(stringOfItemItemToDataFrameOfItemItem[item_item_dependent_var_counter,1],x<-stringOfItemItemToDataFrameOfItemItem,item__table,regr_type<-"ii")
item_cat_fit<-lm(as.numeric(item_item_table$i1) ~
as.numeric(item_item_table$i2) )
item_cat_fit<-lm(as.numeric(item_item_table[item_item_dependent_var_counter])
~ as.numeric(item_item_table[item_item_independent_var_counter ] ) )
#print(summary(item_item_fit))
}
}
How can the lm() arguments be generated dynamically.?Would be grateful if
anyone can come up with a solution for my problem.
--
Thanks
Moumita
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