Skip to contents

S3 methods for fitted freqTLS models

Source: R/methods.R
profile_tls-methods.Rd

Standard extractor and display methods for the profile_tls object returned by fit_tls(): print, summary, coef, vcov, logLik, AIC, and nobs. They mirror the drmTMB method idioms (drmTMB::R/methods.R:2-40,1826-1864,2025-2037).

Usage

# S3 method for class 'profile_tls'
print(x, digits = 4, ...)

# S3 method for class 'profile_tls'
summary(object, ...)

# S3 method for class 'summary.profile_tls'
print(x, digits = 4, ...)

# S3 method for class 'profile_tls'
coef(object, complete = FALSE, ...)

# S3 method for class 'profile_tls'
vcov(object, ...)

# S3 method for class 'profile_tls'
logLik(object, ...)

# S3 method for class 'profile_tls'
AIC(object, ..., k = 2)

# S3 method for class 'profile_tls'
nobs(object, ...)

Arguments

x

A profile_tls fit from fit_tls().

digits

Number of significant digits for the estimates table.

...

Ignored.

object

A profile_tls fit from fit_tls().

complete

Logical; return the full estimates data frame instead of a named vector.

k

Penalty per parameter (default 2, giving the AIC).

Value

print and summary return their input invisibly / the summary object; the extractors return the quantities named in their titles.

Functions

  • print(profile_tls): Print a compact, readable summary: the call, the family, tref, the data summary, the natural-scale estimates table, and the convergence state.

  • summary(profile_tls): Build a summary.profile_tls object carrying the estimates table (with Wald z-statistics and p-values), the family, tref, the data summary, and the convergence state.

  • print(summary.profile_tls): Print a summary.profile_tls object.

  • coef(profile_tls): Extract natural-scale point estimates. With complete = FALSE (default) a named numeric vector; with complete = TRUE the full estimates data frame (parameter, group, estimate, std.error).

  • vcov(profile_tls): The variance-covariance matrix of the internal (unconstrained) coordinates, from TMB::sdreport(). Returns NULL (with a warning) when the sdreport did not produce a covariance.

  • logLik(profile_tls): The maximised log-likelihood, as a logLik object with df and nobs attributes so stats::AIC() and stats::BIC() work.

  • AIC(profile_tls): Akaike's An Information Criterion. With the default k = 2 this returns the stored AIC; other k are computed from the log-likelihood and df.

  • nobs(profile_tls): The number of observations (temperature-by- duration cells) used in the fit.

Examples

d <- simulate_tls(family = "binomial", CTmax = 36, z = 4, seed = 1)
fit <- fit_tls(
  d, y = survived, n = total, time = duration, temp = temp,
  family = "binomial", tref = 1, quiet = TRUE
)
coef(fit)
#>         low          up           k       CTmax           z 
#>  0.01990609  0.97732873  4.89170992 35.92586046  3.99803066 
logLik(fit)
#> 'log Lik.' -129.0538 (df=5)
AIC(fit)
#> [1] 268.1076
nobs(fit)
#> [1] 105