Additional families compatible with sdmTMB().
Usage
Beta(link = "logit")
lognormal(link = "log")
gamma_mix(link = "log")
lognormal_mix(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_gamma_mix(link1 = "logit", link2 = "log")
delta_lognormal(link1 = "logit", link2 = "log")
delta_lognormal_mix(link1 = "logit", link2 = "log")
delta_truncated_nbinom2(link1 = "logit", link2 = "log")
delta_truncated_nbinom1(link1 = "logit", link2 = "log")
delta_poisson_link_gamma(link1 = "log", link2 = "log")
delta_poisson_link_lognormal(link1 = "log", link2 = "log")
delta_beta(link1 = "logit", link2 = "logit")Arguments
- link
Link.
- df
Student-t degrees of freedom fixed value parameter.
- link1
Link for first part of delta/hurdle model.
- link2
Link for second part of delta/hurdle model.
Value
A list with elements common to standard R family objects including family,
link, linkfun, and linkinv.
Details
The families ending in _mix() are 2-component mixtures where each
distribution has its own mean but a shared scale parameter.
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).
For student(), the degrees of freedom parameter is currently not estimated and is fixed at df.
delta_poisson_link_gamma() is the Poisson-link (complementary
log-log) delta model (Thorson 2018).
delta_poisson_link_lognormal() is the Poisson-link (complementary
log-log) delta model (Thorson 2018).
References
Hilbe, J. M. (2011). Negative binomial regression. Cambridge University Press.
Thorson, J. T. (2018). Three problems with the conventional delta-model for biomass sampling data, and a computationally efficient alternative. Canadian Journal of Fisheries and Aquatic Sciences, 75(9), 1369-1382. doi:10.1139/cjfas-2017-0266
Examples
Beta(link = "logit")
#>
#> Family: Beta
#> Link function: logit
#>
lognormal(link = "log")
#>
#> Family: lognormal
#> Link function: log
#>
gamma_mix(link = "log")
#>
#> Family: gamma_mix
#> Link function: log
#>
lognormal_mix(link = "log")
#>
#> Family: lognormal_mix
#> 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_gamma_mix()
#> [[1]]
#>
#> Family: binomial
#> Link function: logit
#>
#>
#> [[2]]
#>
#> Family: gamma_mix
#> Link function: log
#>
#>
#> $delta
#> [1] TRUE
#>
#> $link
#> [1] "logit" "log"
#>
#> $family
#> [1] "binomial" "gamma_mix"
#>
#> $clean_name
#> [1] "delta_gamma_mix(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_lognormal_mix()
#> [[1]]
#>
#> Family: binomial
#> Link function: logit
#>
#>
#> [[2]]
#>
#> Family: lognormal
#> Link function: log
#>
#>
#> $delta
#> [1] TRUE
#>
#> $link
#> [1] "logit" "log"
#>
#> $family
#> [1] "binomial" "lognormal_mix"
#>
#> $clean_name
#> [1] "delta_lognormal_mix(link1 = 'logit', link2 = 'log')"
#>
delta_truncated_nbinom2()
#> [[1]]
#>
#> Family: binomial
#> Link function: logit
#>
#>
#> [[2]]
#> [[2]]$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')"
#>
delta_poisson_link_gamma()
#> [[1]]
#>
#> Family: binomial
#> Link function: log
#>
#>
#> [[2]]
#>
#> Family: Gamma
#> Link function: log
#>
#>
#> $delta
#> [1] TRUE
#>
#> $link
#> [1] "log" "log"
#>
#> $family
#> [1] "binomial" "Gamma"
#>
#> $type
#> [1] "poisson_link_delta"
#>
#> $clean_name
#> [1] "delta_poisson_link_gamma(link1 = 'log', link2 = 'log')"
#>
delta_poisson_link_lognormal()
#> [[1]]
#>
#> Family: binomial
#> Link function: log
#>
#>
#> [[2]]
#>
#> Family: lognormal
#> Link function: log
#>
#>
#> $delta
#> [1] TRUE
#>
#> $link
#> [1] "log" "log"
#>
#> $family
#> [1] "binomial" "lognormal"
#>
#> $type
#> [1] "poisson_link_delta"
#>
#> $clean_name
#> [1] "delta_poisson_link_lognormal(link1 = 'log', link2 = 'log')"
#>
delta_beta()
#> [[1]]
#>
#> Family: binomial
#> Link function: logit
#>
#>
#> [[2]]
#>
#> Family: Beta
#> Link function: logit
#>
#>
#> $delta
#> [1] TRUE
#>
#> $link
#> [1] "logit" "logit"
#>
#> $family
#> [1] "binomial" "Beta"
#>
#> $clean_name
#> [1] "delta_beta(link1 = 'logit', link2 = 'logit')"
#>