Dear All,
When using the spatial linear regression model slm() it produces
"correlation of coefficient estimates" (see example below);
(1) what kind of correlation is this? a Pearson or spearman correlations
coefficient r?
(2) what would be the accepted way to get the slm() to produce
an R-squared?
Example summary:
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Residuals:
Min 1Q Median 3Q Max
-12 2 8 13 30
Coefficients:
Value std error t value Pr(>|t|)
(Intercept) 1.6 0.2364 6.23 0.0000
my.variable1 0.9 0.4927 4.29 0.0010
my.variable2 0.3 0.1038 7.93 0.0000
Residual standard error: 34.1745 on 96 degrees of freedom
Variance-Covariance matrix of Coefficient
(Intercept) my.variable1 my.variable2
(Intercept) 0.055 0.023 0.003
my.variable1 0.001 0.001 0.002
my.variable2 0.001 0.001 0.001
Correlation of coefficient estimates
(Intercept) my.variable1 my.variable2
(Intercept) 1 ? ?
my.variable1 ? 1 ?
my.variable2 ? ? 1
rho = 0.6434
Iterations = 9
gradient norm = 4.532e-7
Log-likelihood = -200.4
Convergence: RELATIVE FUNCTION CONVERGENCE
----------------end of example------------------------------
Thank you in advance for your consideration.
Bernhard
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