Print fitted model objects and summaries.
# S3 method for splm
print(x, digits = max(3L, getOption("digits") - 3L), ...)
# S3 method for spautor
print(x, digits = max(3L, getOption("digits") - 3L), ...)
# S3 method for summary.splm
print(
x,
digits = max(3L, getOption("digits") - 3L),
signif.stars = getOption("show.signif.stars"),
...
)
# S3 method for summary.spautor
print(
x,
digits = max(3L, getOption("digits") - 3L),
signif.stars = getOption("show.signif.stars"),
...
)
# S3 method for anova.splm
print(
x,
digits = max(getOption("digits") - 2L, 3L),
signif.stars = getOption("show.signif.stars"),
...
)
# S3 method for anova.spautor
print(
x,
digits = max(getOption("digits") - 2L, 3L),
signif.stars = getOption("show.signif.stars"),
...
)
# S3 method for spglm
print(x, digits = max(3L, getOption("digits") - 3L), ...)
# S3 method for spgautor
print(x, digits = max(3L, getOption("digits") - 3L), ...)
# S3 method for summary.spglm
print(
x,
digits = max(3L, getOption("digits") - 3L),
signif.stars = getOption("show.signif.stars"),
...
)
# S3 method for summary.spgautor
print(
x,
digits = max(3L, getOption("digits") - 3L),
signif.stars = getOption("show.signif.stars"),
...
)
# S3 method for anova.spglm
print(
x,
digits = max(getOption("digits") - 2L, 3L),
signif.stars = getOption("show.signif.stars"),
...
)
# S3 method for anova.spgautor
print(
x,
digits = max(getOption("digits") - 2L, 3L),
signif.stars = getOption("show.signif.stars"),
...
)A fitted model object from splm(), spautor(), spglm(), or spgautor() or output from
summary(x) or or anova(x).
The number of significant digits to use when printing.
Other arguments passed to or from other methods.
Logical. If TRUE, significance stars are printed for each coefficient
Printed fitted model objects and summaries with formatting.
spmod <- splm(z ~ water + tarp,
data = caribou,
spcov_type = "exponential", xcoord = x, ycoord = y
)
print(spmod)
#>
#> Call:
#> splm(formula = z ~ water + tarp, data = caribou, spcov_type = "exponential",
#> xcoord = x, ycoord = y)
#>
#>
#> Coefficients (fixed):
#> (Intercept) waterY tarpnone tarpshade
#> 2.04981 -0.08310 0.08005 0.28654
#>
#>
#> Coefficients (exponential spatial covariance):
#> de ie range
#> 0.1109 0.0226 19.1168
#>
print(summary(spmod))
#>
#> Call:
#> splm(formula = z ~ water + tarp, data = caribou, spcov_type = "exponential",
#> xcoord = x, ycoord = y)
#>
#> Residuals:
#> Min 1Q Median 3Q Max
#> -0.41281 -0.20763 -0.11205 0.02956 0.45429
#>
#> Coefficients (fixed):
#> Estimate Std. Error z value Pr(>|z|)
#> (Intercept) 2.04981 0.31093 6.592 4.33e-11 ***
#> waterY -0.08310 0.06449 -1.289 0.197563
#> tarpnone 0.08005 0.07759 1.032 0.302166
#> tarpshade 0.28654 0.07667 3.737 0.000186 ***
#> ---
#> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
#>
#> Pseudo R-squared: 0.3963
#>
#> Coefficients (exponential spatial covariance):
#> de ie range
#> 0.1109 0.0226 19.1168
print(anova(spmod))
#> Analysis of Variance Table
#>
#> Response: z
#> Df Chi2 Pr(>Chi2)
#> (Intercept) 1 43.4600 4.327e-11 ***
#> water 1 1.6603 0.1975631
#> tarp 2 15.4071 0.0004512 ***
#> ---
#> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1