22surv_reg_arg_key <- data.frame (
33 flexsurv = c(" dist" ),
44 survreg = c(" dist" ),
5- stan = c(" family" ),
65 stringsAsFactors = FALSE ,
76 row.names = c(" dist" )
87)
@@ -12,7 +11,6 @@ surv_reg_modes <- "regression"
1211surv_reg_engines <- data.frame (
1312 flexsurv = TRUE ,
1413 survreg = TRUE ,
15- stan = TRUE ,
1614 stringsAsFactors = TRUE ,
1715 row.names = c(" regression" )
1816)
@@ -91,32 +89,32 @@ surv_reg_survreg_data <-
9189
9290# ------------------------------------------------------------------------------
9391
94- surv_reg_stan_data <-
95- list (
96- libs = c(" brms" ),
97- fit = list (
98- interface = " formula" ,
99- protect = c(" formula" , " data" , " weights" ),
100- func = c(pkg = " brms" , fun = " brm" ),
101- defaults = list (
102- family = expr(brms :: weibull()),
103- seed = expr(sample.int(10 ^ 5 , 1 ))
104- )
105- ),
106- pred = list (
107- pre = NULL ,
108- post = function (results , object ) {
109- tibble :: as_tibble(results ) %> %
110- dplyr :: select(Estimate ) %> %
111- setNames(" .pred" )
112- },
113- func = c(fun = " predict" ),
114- args =
115- list (
116- object = expr(object $ fit ),
117- newdata = expr(new_data ),
118- type = " response"
119- )
120- )
121- )
92+ # surv_reg_stan_data <-
93+ # list(
94+ # libs = c("brms"),
95+ # fit = list(
96+ # interface = "formula",
97+ # protect = c("formula", "data", "weights"),
98+ # func = c(pkg = "brms", fun = "brm"),
99+ # defaults = list(
100+ # family = expr(brms::weibull()),
101+ # seed = expr(sample.int(10^5, 1))
102+ # )
103+ # ),
104+ # pred = list(
105+ # pre = NULL,
106+ # post = function(results, object) {
107+ # tibble::as_tibble(results) %>%
108+ # dplyr::select(Estimate) %>%
109+ # setNames(".pred")
110+ # },
111+ # func = c(fun = "predict"),
112+ # args =
113+ # list(
114+ # object = expr(object$fit),
115+ # newdata = expr(new_data),
116+ # type = "response"
117+ # )
118+ # )
119+ # )
122120
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