I have a dataset of Populus Alba trees distribution in Hungary. I made a ppm model and used temperature, elevation and precipitation as covariates (this is the code: ppm1_alba <- ppm(p_alba_ppp ~ temp_im_hungary + prec_im_hungary + elevation_im_hungary). I need to estimate the effect of the temperature, elevation and precipitation on the distribution of tress. I used ppm model because I'm using spatstat package.I used a "ppp" object to built the model and covariates are "im" objects. I don't exactly know how to interpret the result as there is no Pvalue. Could anyone help me?

```
Fitted trend coefficients:
(Intercept) temp_im_hungary prec_im_hungary elevation_im_hungary
-25.12321300 0.25118693 0.00582099 -0.04465693
Estimate S.E. CI95.lo CI95.hi Ztest
(Intercept) -25.12321300 3.415243260 -31.816966783 -18.42945921 ***
temp_im_hungary 0.25118693 0.325343625 -0.386474861 0.88884871
prec_im_hungary 0.00582099 0.002262749 0.001386084 0.01025590 *
elevation_im_hungary -0.04465693 0.012035001 -0.068245104 -0.02106877 ***
Zval
(Intercept) -7.3562002
temp_im_hungary 0.7720665
prec_im_hungary 2.5725306
elevation_im_hungary -3.7105883
```