Extract model coefficients

Returns coefficients on the response scale (i.e. exponentiated linear- predictor coefficients) as a named numeric vector, matching the convention of stats::coef(). For zero-inflated models the count and zero-inflation components are concatenated into a single vector with count_ and zero_ name prefixes, mirroring pscl::zeroinfl().

Usage

# S3 method for class 'countGLMfit'
coef(object, ...)

# S3 method for class 'zeroinflGLMfit'
coef(object, component = c("both", "count", "zero"), ...)

# S3 method for class 'countGLM'
coef(object, ...)

Arguments

object

A fitted model object of class countGLMfit or zeroinflGLMfit.

...

Unused.

component

For zero-inflated models, "both" (default) returns the concatenated vector; "count" returns only the count component; "zero" returns only the zero-inflation component.

Value

A named numeric vector of exponentiated coefficients.

Details

Use coef_table() to get the full coefficient table including 95\ CIs, p-values, and significance stars.

Examples

df <- data.frame(
  y  = c(0L, 1L, 2L, 3L, 5L, 0L, 2L, 4L, 1L, 3L),
  x1 = c(1.2, -0.4, 0.8, -1.1, 2.0, 0.3, -0.9, 1.5, -0.2, 0.7)
)
fit <- poissonGLM(y ~ x1, data = df)
#> Warning: Count component: 8 events (y > 0) for 1 predictor(s) (8.0 per predictor). At least 10 events per predictor is recommended.
coef(fit)
#> (Intercept)          x1 
#>    1.798861    1.339607 
coef_table(fit)
#>          term exp.coef lower.95 upper.95    p.value stars
#> 1 (Intercept) 1.798861 1.068297 3.029027 0.02721241     *
#> 2          x1 1.339607 0.857165 2.093584 0.19934617