我正在阅读《Integrated Inferences》这本书，该书使用 R 库 CausalQueries 来执行示例计算。 如标题所述，许多其他 CausalQueries 函数运行良好，但我收到一条错误消息，提示“无法找到函数“get_type_prob”。”
我昨天安装了 Windows 版 R 4.4，并将 CausalQueries 库安装在用户特定的文件夹中（因为 R 包管理器无法将其添加到系统安装中。我使用库（CausalQueries）将其加载到工作区中，验证它是否出现在 search() 结果中，并且对其他库函数的前几个函数调用起作用。
完成此示例，一次将其粘贴到表达式中：
`model <- make_model("X -> M -> Y") |>
set_restrictions("X[]==0") |>
set_restrictions("M[X=1] < M[X=0]") |>
set_restrictions("Y[M=1] < Y[M=0]")
q1 <- "Y[X = 1] > Y[X = 0]"
q2 <- "X == 1 & Y == 1"
df <- data.frame(
a1 = get_query_types(model, q1)$types,
a2 = get_query_types(model, q2)$types,
p = get_type_prob(model))`
我希望这能起作用，并提供 CausalQueries 文档中表格的数据。全场：
> library(CausalQueries)
Loading required package: dplyr
Attaching package: ‘dplyr’
The following objects are masked from ‘package:stats’:
filter, lag
The following objects are masked from ‘package:base’:
intersect, setdiff, setequal, union
Loading required package: Rcpp
> model <- make_model("X -> M -> Y") |>
+ set_restrictions("X[]==0") |>
+ set_restrictions("M[X=1] < M[X=0]") |>
+ set_restrictions("Y[M=1] < Y[M=0]")
>
> q1 <- "Y[X = 1] > Y[X = 0]"
> q2 <- "X == 1 & Y == 1"
>
> df <- data.frame(
+ a1 = get_query_types(model, q1)$types,
+ a2 = get_query_types(model, q2)$types,
+ p = get_type_prob(model))
Error in get_type_prob(model) : could not find function "get_type_prob"
> ls("package:CausalQueries")
[1] "collapse_data" "complements"
[3] "data_type_names" "decreasing"
[5] "democracy_data" "draw_causal_type"
[7] "expand_data" "expand_wildcard"
[9] "get_all_data_types" "get_event_probabilities"
[11] "get_query_types" "grab"
[13] "increasing" "institutions_data"
[15] "interacts" "interpret_type"
[17] "lipids_data" "make_data"
[19] "make_events" "make_model"
[21] "make_parameters" "make_parameters_df"
[23] "make_prior_distribution" "make_priors"
[25] "non_decreasing" "non_increasing"
[27] "observe_data" "plot_model"
[29] "query_distribution" "query_model"
[31] "realise_outcomes" "set_confound"
[33] "set_parameter_matrix" "set_parameters"
[35] "set_prior_distribution" "set_priors"
[37] "set_restrictions" "simulate_data"
[39] "substitutes" "te"
[41] "update_model"