Additional families compatible with sdmTMB()
.
Beta(link = "logit")
lognormal(link = "log")
nbinom2(link = "log")
nbinom1(link = "log")
truncated_nbinom2(link = "log")
truncated_nbinom1(link = "log")
student(link = "identity", df = 3)
tweedie(link = "log")
censored_poisson(link = "log")
delta_gamma(link1 = "logit", link2 = "log")
delta_lognormal(link1 = "logit", link2 = "log")
delta_truncated_nbinom2(link1 = "logit", link2 = "log")
delta_truncated_nbinom1(link1 = "logit", link2 = "log")
Link.
Student-t degrees of freedom fixed value parameter.
Link for first part of delta/hurdle model.
Link for second part of delta/hurdle model.
A list with elements common to standard R family objects including family
,
link
, linkfun
, and linkinv
.
The nbinom2
negative binomial parameterization is the NB2 where the variance grows
quadratically with the mean (Hilbe 2011).
The nbinom1
negative binomial parameterization lets the variance grow
linearly with the mean (Hilbe 2011).
The degrees of freedom parameter is currently not estimated and is fixed at df
.
Hilbe, J. M. (2011). Negative binomial regression. Cambridge University Press.
Beta(link = "logit")
#>
#> Family: Beta
#> Link function: logit
#>
lognormal(link = "log")
#>
#> Family: lognormal
#> Link function: log
#>
nbinom2(link = "log")
#>
#> Family: nbinom2
#> Link function: log
#>
nbinom1(link = "log")
#>
#> Family: nbinom1
#> Link function: log
#>
truncated_nbinom2(link = "log")
#> $family
#> [1] "truncated_nbinom2"
#>
#> $link
#> [1] "log"
#>
#> $linkfun
#> function (mu)
#> log(mu)
#> <environment: namespace:stats>
#>
#> $linkinv
#> function (eta)
#> pmax(exp(eta), .Machine$double.eps)
#> <environment: namespace:stats>
#>
truncated_nbinom1(link = "log")
#> $family
#> [1] "truncated_nbinom1"
#>
#> $link
#> [1] "log"
#>
#> $linkfun
#> function (mu)
#> log(mu)
#> <environment: namespace:stats>
#>
#> $linkinv
#> function (eta)
#> pmax(exp(eta), .Machine$double.eps)
#> <environment: namespace:stats>
#>
student(link = "identity")
#>
#> Family: student
#> Link function: identity
#>
tweedie(link = "log")
#>
#> Family: tweedie
#> Link function: log
#>
censored_poisson(link = "log")
#> $family
#> [1] "censored_poisson"
#>
#> $link
#> [1] "log"
#>
#> $linkfun
#> function (mu)
#> log(mu)
#> <environment: namespace:stats>
#>
#> $linkinv
#> function (eta)
#> pmax(exp(eta), .Machine$double.eps)
#> <environment: namespace:stats>
#>
delta_gamma()
#> [[1]]
#>
#> Family: binomial
#> Link function: logit
#>
#>
#> [[2]]
#>
#> Family: Gamma
#> Link function: log
#>
#>
#> $delta
#> [1] TRUE
#>
#> $link
#> [1] "logit" "log"
#>
#> $family
#> [1] "binomial" "Gamma"
#>
#> $clean_name
#> [1] "delta_gamma(link1 = 'logit', link2 = 'log')"
#>
delta_lognormal()
#> [[1]]
#>
#> Family: binomial
#> Link function: logit
#>
#>
#> [[2]]
#>
#> Family: lognormal
#> Link function: log
#>
#>
#> $delta
#> [1] TRUE
#>
#> $link
#> [1] "logit" "log"
#>
#> $family
#> [1] "binomial" "lognormal"
#>
#> $clean_name
#> [1] "delta_lognormal(link1 = 'logit', link2 = 'log')"
#>
delta_truncated_nbinom2()
#> [[1]]
#>
#> Family: binomial
#> Link function: logit
#>
#>
#> [[2]]
#> [[2]]$family
#> [1] "truncated_nbinom2"
#>
#> [[2]]$link
#> [1] "log"
#>
#> [[2]]$linkfun
#> function (mu)
#> log(mu)
#> <environment: namespace:stats>
#>
#> [[2]]$linkinv
#> function (eta)
#> pmax(exp(eta), .Machine$double.eps)
#> <environment: namespace:stats>
#>
#>
#> $delta
#> [1] TRUE
#>
#> $link
#> [1] "logit" "log"
#>
#> $family
#> [1] "binomial" "truncated_nbinom2"
#>
#> $clean_name
#> [1] "delta_truncated_nbinom2(link1 = 'logit', link2 = 'log')"
#>
delta_truncated_nbinom1()
#> [[1]]
#>
#> Family: binomial
#> Link function: logit
#>
#>
#> [[2]]
#> [[2]]$family
#> [1] "truncated_nbinom1"
#>
#> [[2]]$link
#> [1] "log"
#>
#> [[2]]$linkfun
#> function (mu)
#> log(mu)
#> <environment: namespace:stats>
#>
#> [[2]]$linkinv
#> function (eta)
#> pmax(exp(eta), .Machine$double.eps)
#> <environment: namespace:stats>
#>
#>
#> $delta
#> [1] TRUE
#>
#> $link
#> [1] "logit" "log"
#>
#> $family
#> [1] "binomial" "truncated_nbinom1"
#>
#> $clean_name
#> [1] "delta_truncated_nbinom1(link1 = 'logit', link2 = 'log')"
#>