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Print a model summary (betareg style)

Source: R/methods.R
print.summary.brs.Rd

Print a model summary (betareg style)

Usage

# S3 method for class 'summary.brs'
print(x, digits = max(3, getOption("digits") - 3), ...)

Arguments

x

A "summary.betaregscale" object.

digits

Number of digits.

...

Passed to printCoefmat.

Value

Invisibly returns the input object x. The function is called for its side effect of printing a comprehensive summary to the console, including the model call, quantile residuals, coefficient tables for mean and precision submodels with significance stars, goodness-of-fit statistics (log-likelihood, pseudo R-squared), optimization details, and censoring information.

See also

summary.brs, brs, print.brs

Examples

# \donttest{
dat <- data.frame(
  y = c(
    0, 5, 20, 50, 75, 90, 100, 30, 60, 45,
    10, 40, 55, 70, 85, 25, 35, 65, 80, 15
  ),
  x1 = rep(c(1, 2), 10)
)
prep <- brs_prep(dat, ncuts = 100)
#> brs_prep: n = 20 | exact = 0, left = 1, right = 1, interval = 18
fit <- brs(y ~ x1, data = prep)
print(summary(fit))
#> 
#> Call:
#> brs(formula = y ~ x1, data = prep)
#> 
#> Quantile residuals:
#>     Min      1Q  Median      3Q     Max 
#> -2.6342 -0.4820  0.0653  0.5357  2.8625 
#> 
#> Coefficients (mean model with logit link):
#>             Estimate Std. Error z value Pr(>|z|)
#> (Intercept)   0.2551     0.8644   0.295    0.768
#> x1           -0.2202     0.5412  -0.407    0.684
#> 
#> Phi coefficients (precision model with logit link):
#>       Estimate Std. Error z value Pr(>|z|)
#> (phi)  -0.3929     0.2763  -1.422    0.155
#> ---
#> Log-likelihood: -92.6521 on 3 Df | AIC: 191.3041 | BIC: 194.2913 
#> Pseudo R-squared: 0.0029 
#> Number of iterations: 17 (BFGS) 
#> Censoring: 18 interval | 1 left | 1 right 
#> 
# }