View source: R/control_inference.R
control_inf | R Documentation |
control_inf
constructs a list
with all necessary control parameters
for statistical inference.
control_inf(
var_method = c("analytic", "bootstrap"),
rep_type = c("subbootstrap", "auto", "JK1", "JKn", "BRR", "bootstrap", "mrbbootstrap",
"Fay"),
vars_selection = FALSE,
vars_combine = FALSE,
bias_correction = FALSE,
num_boot = 500,
alpha = 0.05,
cores = 1,
keep_boot = TRUE,
nn_exact_se = FALSE
)
var_method |
the variance method (default |
rep_type |
the replication type for weights in the bootstrap method for variance estimation passed to |
vars_selection |
default |
vars_combine |
whether variables should be combined after variable selection for doubly robust estimators (default |
bias_correction |
default |
num_boot |
the number of iteration for bootstrap algorithms. |
alpha |
significance level (default 0.05). |
cores |
the number of cores in parallel computing (default 1). |
keep_boot |
a logical value indicating whether statistics from bootstrap should be kept (default |
nn_exact_se |
a logical value indicating whether to compute the exact
standard error estimate for |
A list
with selected parameters.
nonprob()
– for fitting procedure with non-probability samples.
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