Nonparametric regression using kernel weights

I am wondering how I can present the results of nonparametric regression. I performed the nonparametric tests using R, and R package 'np'.

The commands used for this are
> freq <- npreg(Respno ~ Colony + Localden + Agg.prop, regtype = "ll",bwmethod = "cv.aic",gradients = TRUE, data = resp)
> summary(freq2)
> npsigtest(freq2

Using the last command, 'npsigtest', I get results like this
> npsigtest(freq)

Kernel Regression Significance Test
Type I Test with IID Bootstrap (399 replications, Pivot = TRUE, joint = FALSE)
Explanatory variables tested for significance:
Colony (1), Localden (2), Agg.prop (3)

Colony Localden Agg.prop
Bandwidth(s): 21.88052 5956578 0.3183519

Individual Significance Tests
P Value:
Colony 0.0025063 **
Localden < 2.22e-16 ***
Agg.prop 0.0802005 .
How do I present this data in a scientific paper? For the simple linear regression results, I included the n, df, t and P.

Thank you, any advice would be greatly appreciated!!