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Summarize a fitted model

Source: R/methods.R
summary.drmTMB.Rd

summary() returns a compact summary of fixed-effect estimates, response-scale distributional, scale, shape, random-effect SD, correlation, and fitted random-effect covariance quantities when they are present. The covariance component reports currently fitted registry-backed rows and the first fitted bivariate phylogenetic mu1/mu2 mean-mean row. The derived component reports simple point-estimate variance ratios, such as Gaussian random-intercept repeatability and phylogenetic signal, when the ingredients are unambiguous. Derived confidence intervals are marked as unavailable until a nonlinear interval method is implemented. When TMB::sdreport() succeeds, direct response-scale parameter rows also include delta-method standard errors; descriptive fitted ranges and derived variance ratios do not. Confidence intervals are opt-in: fast Wald intervals are available for fixed effects, and slower profile-likelihood intervals are available for selected direct profile targets. Profile summaries keep Wald intervals for fixed effects unless fixed-effect profile targets are selected. Interval-aware tables include conf.status so rows without intervals can say whether an interval was not requested, needs newdata, is ready but unselected, or is currently unavailable. Use summary(fit, conf.int = TRUE) for fixed-effect Wald confidence intervals, and use method = "profile" with ci_parm for direct response-scale targets such as sigma, rho12, or a random-effect SD.

Usage

# S3 method for class 'drmTMB'
summary(
  object,
  conf.int = FALSE,
  level = 0.95,
  method = c("wald", "profile"),
  ci_parm = NULL,
  trace = FALSE,
  ...
)

Arguments

object

A drmTMB fit.

conf.int

Logical; include confidence intervals when TRUE.

level

Confidence level for intervals.

method

Interval method used when conf.int = TRUE: "wald" for fixed-effect intervals or "profile" for profile-likelihood intervals on selected direct targets. Parametric bootstrap intervals are not implemented yet.

ci_parm

Optional character or integer vector selecting confidence interval targets. For method = "wald", targets must be fixed effects. For method = "profile", targets use the profile_targets() namespace, such as "sigma", "rho12", "sd:mu:(1 | id)", or "cor:mu:cor((Intercept),x | id)". NULL selects all fixed effects for Wald intervals and all currently ready direct targets for profile intervals.

trace

Logical; passed to TMB::tmbprofile() for profile intervals.

...

Additional arguments passed to TMB::tmbprofile() when conf.int = TRUE and method = "profile".

Value

An object of class summary.drmTMB.

Examples

dat <- data.frame(y = c(0.2, 0.5, 1.1, 1.4), x = c(-1, 0, 1, 2))
fit <- drmTMB(bf(y ~ x, sigma ~ 1), data = dat)
summary(fit)
#> <summary.drmTMB>
#>                    estimate  std_error
#> mu:(Intercept)     0.590000 0.03674236
#> mu:x               0.420000 0.03000001
#> sigma:(Intercept) -2.701838 0.35355344
#> Distributional, random-effect, scale, and correlation parameters:
#>                  component  dpar       term   estimate std_error    scale
#> sigma distributional-scale sigma (constant) 0.06708207 0.0237171 response
#> logLik: 5.132
#> convergence: 0
summary(fit, conf.int = TRUE)
#> <summary.drmTMB>
#> confidence intervals: wald, level = 0.95
#>                    estimate  std_error   conf.low  conf.high conf.level
#> mu:(Intercept)     0.590000 0.03674236  0.5179863  0.6620137       0.95
#> mu:x               0.420000 0.03000001  0.3612011  0.4787990       0.95
#> sigma:(Intercept) -2.701838 0.35355344 -3.3947905 -2.0088865       0.95
#>                   conf.method conf.status profile.boundary profile.message
#> mu:(Intercept)           wald        wald               NA            <NA>
#> mu:x                     wald        wald               NA            <NA>
#> sigma:(Intercept)        wald        wald               NA            <NA>
#> Distributional, random-effect, scale, and correlation parameters:
#>                  component  dpar       term   estimate std_error    scale
#> sigma distributional-scale sigma (constant) 0.06708207 0.0237171 response
#>            conf.status
#> sigma wald_unavailable
#> logLik: 5.132
#> convergence: 0
summary(fit, conf.int = TRUE, method = "profile", ci_parm = "sigma")
#> <summary.drmTMB>
#> confidence intervals: profile, level = 0.95
#>                    estimate  std_error   conf.low  conf.high conf.level
#> mu:(Intercept)     0.590000 0.03674236  0.5179863  0.6620137       0.95
#> mu:x               0.420000 0.03000001  0.3612011  0.4787990       0.95
#> sigma:(Intercept) -2.701838 0.35355344 -3.3947905 -2.0088865       0.95
#>                   conf.method conf.status profile.boundary profile.message
#> mu:(Intercept)           wald        wald               NA            <NA>
#> mu:x                     wald        wald               NA            <NA>
#> sigma:(Intercept)        wald        wald               NA            <NA>
#> Distributional, random-effect, scale, and correlation parameters:
#>                  component  dpar       term   estimate std_error    scale
#> sigma distributional-scale sigma (constant) 0.06708207 0.0237171 response
#>         conf.low conf.high
#> sigma 0.03817522 0.1645071
#> logLik: 5.132
#> convergence: 0