R/summary.stratafit.R
summary.stratafit.RdIf a model is fitted with stratafit(), then
this summary function produces summary output for each level
of the stratification variable in the same style as the
summary.slmfit() function.
# S3 method for stratafit
summary(object, ...)is an object generated from slmfit() of class slmfit.
further arguments passed to or from other methods.
a list with
model formula
a table of fixed effects estimates and associated standard errors
estimated spatial covariance parameter estimates
residuals
generalized r-squared.
data(exampledataset) ## load a toy data set
exampledataset$strata <- c(rep("A", 25), rep("B", 15))
strataobj <- stratafit(formula = counts ~ pred1 + pred2,
data = exampledataset, stratacol = "strata",
xcoordcol = 'xcoords', ycoordcol = 'ycoords', areacol = 'areavar')
summary(strataobj)
#> $A
#>
#> Call:
#> counts ~ pred1 + pred2
#>
#> Residuals:
#> Min 1Q Median 3Q Max
#> -9.4506 -2.6459 0.2484 2.9445 10.5560
#>
#> Coefficients:
#> Estimate Std. Error t value Pr(>|t|)
#> (Intercept) 20.6827 2.2953 9.011 <2e-16 ***
#> pred1 -5.1222 3.3304 -1.538 0.142
#> pred2 -0.2208 1.6677 -0.132 0.896
#> ---
#> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
#>
#> Covariance Parameters:
#> Exponential Model
#> Nugget 5.7237151
#> Partial Sill 20.2900151
#> Range 0.7685046
#>
#> Generalized R-squared: 0.1280635
#>
#> $B
#>
#> Call:
#> counts ~ pred1 + pred2
#>
#> Residuals:
#> Min 1Q Median 3Q Max
#> -8.6892 -3.3922 -0.0594 1.8881 12.8373
#>
#> Coefficients:
#> Estimate Std. Error t value Pr(>|t|)
#> (Intercept) 20.931 1039.525 0.020 0.984
#> pred1 2.416 5.099 0.474 0.644
#> pred2 -1.969 1.151 -1.710 0.113
#>
#> Covariance Parameters:
#> Exponential Model
#> Nugget 2.457091e+01
#> Partial Sill 1.080612e+06
#> Range 4.005461e+05
#>
#> Generalized R-squared: 0.20773
#>