[R] Generating nested models for order selection tests

Ready Learner re@dyto|e@rn90 @end|ng |rom gm@||@com
Mon May 27 09:43:42 CEST 2019

Dear Bert,

Thank you for your response. I apologize for getting back to you a little
I do not think that my question is statistical. As a matter of fact, I do
know what I want to do in terms of statistics. The problem is that I do not
know how I can do it via R. To be more precise my question is: Is there a
way to create a sequence of nested models via series expansion (based on a
basis function) in R?

All the best,

On Fri, May 24, 2019 at 6:49 PM Bert Gunter <bgunter.4567 using gmail.com> wrote:

> 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 using 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
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