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> # This file is part of the standard setup for testthat.
> # It is recommended that you do not modify it.
> #
> # Where should you do additional test configuration?
> # Learn more about the roles of various files in:
> # * https://r-pkgs.org/tests.html
> # * https://testthat.r-lib.org/reference/test_package.html#special-files
> 
> library(testthat)
> library(hgwrr)
Loading required package: sf
Linking to GEOS 3.12.1, GDAL 3.8.4, PROJ 9.3.1; sf_use_s2() is TRUE
Loading required package: MASS
> 
> test_check("hgwrr")
Hierarchical and geographically weighted regression model
=========================================================
Formula: y ~ L(g1 + g2) + x1 + (z1 | group)
 Method: Back-fitting and Maximum likelihood
   Data: mulsam.test$data

Fixed Effects
-------------
 Intercept        x1 
  1.852190  1.967644 

Group-level Spatially Weighted Effects
--------------------------------------
Bandwidth: 10 (nearest neighbours)

Coefficient estimates:
 Coefficient        Min  1st Quartile     Median  3rd Quartile       Max 
   Intercept  -0.549094     -0.439522  -0.151433     -0.024133  0.178044 
          g1   0.909293      1.253143   1.692616      1.927313  2.310056 
          g2   1.083410      1.279953   1.415744      1.594576  1.693768 

Sample-level Random Effects
---------------------------
   Groups       Name  Std.Dev.      Corr 
    group  Intercept  1.033171           
                  z1  1.033171  0.000000 
 Residual             1.033171           

Other Information
-----------------
Number of Obs: 873
       Groups: group , 25
Hierarchical and geographically weighted regression model
=========================================================
Formula: y ~ L(g1 + g2) + x1 + (z1 | group)
 Method: Back-fitting and Maximum likelihood
   Data: mulsam.test$data

Fixed Effects
-------------
 Intercept        x1 
  1.852190  1.967644 

Group-level Spatially Weighted Effects
--------------------------------------
Bandwidth: 10 (nearest neighbours)

Coefficient estimates:
 Coefficient        Min  1st Quartile     Median  3rd Quartile       Max 
   Intercept  -0.549094     -0.439522  -0.151433     -0.024133  0.178044 
          g1   0.909293      1.253143   1.692616      1.927313  2.310056 
          g2   1.083410      1.279953   1.415744      1.594576  1.693768 

Sample-level Random Effects
---------------------------
   Groups       Name  Std.Dev.      Corr 
    group  Intercept  1.033171           
                  z1  1.033171  0.000000 
 Residual             1.033171           

Other Information
-----------------
Number of Obs: 873
       Groups: group , 25
Hierarchical and geographically weighted regression model
=========================================================
Formula: y ~ L(g1 + g2) + x1 + (z1 | group)
 Method: Back-fitting and Maximum likelihood
   Data: mulsam.test$data

Parameter Estimates
-------------------
Fixed effects:
            Estimated   Sd. Err      t.val  Pr(>|t|)      
 Intercept   1.852190  0.203079   9.120541  0.000000  *** 
        x1   1.967644  0.033827  58.168539  0.000000  *** 

Bandwidth: 10 (nearest neighbours)

GLSW effects:
            Mean Est.  Mean Sd.   ***    **     *      . 
 Intercept  -0.208441  0.247059  0.0%  0.0%  4.0%  24.0% 
        g1   1.631474  1.795246  0.0%  0.0%  0.0%   0.0% 
        g2   1.430116  1.476570  0.0%  0.0%  0.0%   0.0% 

SLR effects:
   Groups       Name      Mean  Std.Dev.      Corr 
    group  Intercept  0.000000  1.033171           
                  z1  1.869539  1.033171  0.000000 
 Residual             0.079964  1.033171           


Diagnostics
-----------
 rsquared  0.905207 
   logLik       NaN 
      AIC       NaN 

Scaled Residuals
----------------
       Min         1Q    Median        3Q       Max 
 -3.416380  -0.584726  0.092501  0.725766  3.028003 

Other Information
-----------------
Number of Obs: 873
       Groups: group , 25
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[ FAIL 0 | WARN 0 | SKIP 0 | PASS 96 ]
> 
> proc.time()
   user  system elapsed 
  66.01    0.34   66.34