[R] Generating nested models for order selection tests
bgunter@4567 @end|ng |rom gm@||@com
Fri May 24 18:48:48 CEST 2019
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
On Fri, May 24, 2019 at 8:48 AM Ready Learner <readytolearn90 using gmail.com>
> 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,
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