fitnlm and dummy variables

1 visualizzazione (ultimi 30 giorni)
Tania
Tania il 18 Giu 2014
Commentato: the cyclist il 23 Giu 2014
Hi all, Fitnlm allows automatic creation of dummy variables, if one input the categorical predictor as a nominal or ordinal array. It worked fine for me with fitlm. But I do not understand how I know how many input arguments I get after using the automatic creation of dummy variables. As I need to specify my beta0 I need to know how many input arguments I have. Thank you!

Risposta accettata

the cyclist
the cyclist il 18 Giu 2014
Modificato: the cyclist il 18 Giu 2014
I haven't used the automatic creation of dummy variables, so I don't know the answer to your question. However, the dummyvar() function might also be helpful for you, so I thought I'd mention it.
  3 Commenti
Tania
Tania il 23 Giu 2014
Hi, I have created a dummyvar for my postcode variable now: dv=dummyvar(B) But I am not sure how I use this now in fitlm (or fitnlm). Without dummyvar I would do the following: >> ds = dataset(price, bedroom, school, transport); >> mdl =fitlm(ds, 'price~bedroom + school + transport') How do I include my dv now into my dataset? My dv has 29 columns. Thank you! PS: I have my document attached!
the cyclist
the cyclist il 23 Giu 2014
Suppose you have the following grouping variable (where "1", "2", etc represent the groups):
group = [1;1;1;2;2;3;3;3;3;4]
Then
dv = dummyvar(group)
gives
dv =
1 0 0 0
1 0 0 0
1 0 0 0
0 1 0 0
0 1 0 0
0 0 1 0
0 0 1 0
0 0 1 0
0 0 1 0
0 0 0 1
Each column of dv is a variable in your regression. The first column is the binary variable "is_member_of_group?", where 1=yes and 0=no. Likewise for other columns.

Accedi per commentare.

Più risposte (0)

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by