[R] Generating nested models for order selection tests

Bert Gunter
Fri, 24 May 2019 16:48:48 -0000

Purely statistical questions are generally off topic here, and your query
may fall under that rubric. But you should try searching at rseek.org and R
task views -- https://cran.r-project.org/web/views/  -- perhaps under the
SocialScience heading or others that may use the methodology to which you
refer.

Cheers,
Bert

On Fri, May 24, 2019 at 8:48 AM Ready Learner <readytolearn90 at
gmail.com>
wrote:

> Hello everyone,
>
> I have created a parametric additive model for the median house price (as
> the response) and with the number of tax forms (x1) and the number of
> healthcare facilities (x2) as my covariates. I should mention that both of
> the covariates have quadratic effects in my model.
>
> Now I want to do a hypothesis testing. I am taking the mentioned parametric
> model as my null state (hypothesis) and I want to use "order selection
> test" to test it against a nonparametric alternative hypothesis. Based
on
> what I understood from few related articles I have read, I should create a
> sequence of nested models. I am thinking about using polynomial or cosine
> functions as my basis function. In either case, I have to create a series
> of models (i.e. the sequence of nested models via series expansion) based
> on the basis function to test the hypothesis.
> Is there any way to do this automatically in R?
>
> Kind regards,
> readyToLearn
>
>         [[alternative HTML version deleted]]
>
> ______________________________________________
> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>