The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.
DeclareDesign 2.0 is a ground-up reimplementation on tidyverse
primitives. The declaration syntax is unchanged; the changes below are
at the edges. vignette("declaredesign2.0") gives the
reasoning for each and a grep table for porting a script.
redesign() reaches a name the design reads (a value
named above the design, a designer function’s argument, or a
declare_parameters() entry) and no longer a number written
inside a step. redesign(design, N = 1000) over
declare_model(N = 500) errors with the two ways to name the
value; in 1.x it warned and returned the design unchanged.declare_estimator(inquiry = ) takes the inquiry’s label
as a string. Passing the inquiry step object is an error; in 1.x it
linked the estimator to an inquiry called "inquiry" and
returned NA estimands.diagnose_design() and simulate_design()
drop make_groups, add_grouping_variables, and
future.seed, each with an error naming the replacement.
Group with
simulate_design() |> group_by() |> diagnose_design();
seed with set.seed() before the call.redesign()’s first argument is .design and
expand_design()’s is .designer, and both take
.expand after the dots, so a parameter named
expand, or d or any other prefix of
design, is no longer swallowed by partial matching.
expand_design() drops prefix, which named the
designs it returned design_1, design_2, and so
on; designs are now named by the values that distinguish them.draw_data() no longer runs part of a design on supplied
data; data, start, and end are
gone, and passing them stops with an error naming the replacement unless
the design reads a parameter by that name. Use
get_estimates(design, data) to run estimators on supplied
data and design[i:j] for a slice.label_estimator(fn = ) and
label_test(fn = ) are .method =;
set_diagnosands(x = ) is design =;
reshape_diagnosis() drops select and
exclude.compare_designs(), compare_design_code(),
compare_design_summaries(),
compare_design_estimates(),
compare_design_inquiries(),
compare_design_data(), and print_code() are
defunct and say so. compare_diagnoses() stays.declare_potential_outcomes() and
declare_reveal() are defunct;
declare_estimators() is gone.estimand column and
puts estimator, inquiry, and
estimand after the tidied statistics. Two estimators with
one label are renamed apart with a message rather than an error.expand_design() warns once per session; call the
designer and redesign() the result:
redesign(designer(), N = c(100, 200)).set_diagnosands() warns once per session; pass the
diagnosands to the diagnosis instead,
diagnose_design(design, diagnosands = ...). An attached set
replaces the defaults rather than adding to them, and does not survive
redesign(), which now warns when it drops one.insert_step(), delete_step(), and
replace_step() warn once per session; rebuild the design
with design[1:2] + new_step + design[4:5] instead.declare_population(), model_handler(), and
tidy_estimator() warn once per session.declare_estimator(model = ) is read as
.method = with a warning.declare_parameters() names the values a design can be
redesigned over, and declare_notes() names the quantities
it works out along the way; design_parameters() and
design_notes() list them. A declared parameter is bound for
every step after it, including a helper function that reads it.run_design(), draw_data(),
draw_estimands(), and draw_estimates() take
named parameter values, so draw_data(design, theta = 0.5)
draws from a declaration that leaves theta free (closes
#497). The values go through redesign(), so the rules about
which names a design accepts are stated in one place, and supplying
several values is refused rather than narrowed: sweep with
redesign() and draw from each.saveRDS(), reaches a parallel worker, and does
not change meaning when a workspace variable is edited (closes
#293).draws fan a step out and hold everything
upstream fixed; the diagnosis of such a design carries a
variance_decomposition attributing the variance of each
per-simulation quantity to the step that generated it.simulate_design() is recorded as a row with
error = TRUE, one warning per run gives the counts, and
diagnosands use the draws that succeeded (closes #385).
run_design() and draw_estimates() still
stop.future::plan(), so a seeded run gives the same table
sequentially and in parallel, and the caller’s own generator is left in
the same place either way: one draw on, whichever plan is active (closes
#445). furrr draws a value from the caller’s stream
whenever it is handed a seed, so a parallel run used to leave it one
uniform further on than a sequential one.progress = TRUE on simulate_design() and
diagnose_design(), or
progressr::handlers(global = TRUE) once per session,
reports progress through progressr, from parallel workers too.print(design) shows the calls that declared the steps,
as 1.x did, and the parameters redesign() can reach.
summary(design) runs the design once and says under each
step what it did to the data (rows kept, columns added, dropped or
changed, the estimand, the estimate), returning the pieces as a
summary.design object; run = FALSE skips the
run.diagnose_design() accepts a simulations data frame in
place of a design and honours its grouping.
diagnose_simulations() does the same thing under a name
that says what the argument is.default_diagnosands() and
select_diagnosands() build a diagnosands set from names;
tidy() works on a diagnosis..method or the
handler as written, so methods that do their own non-standard evaluation
work (closes #463; also #456, #457, #482, #509).declare_measurement(),
declare_assignment(), or declare_sampling()
step that supplies its own rows, rather than receiving them from the
model, no longer appends a row id column. 1.x asked for this at every
call site but never passed the flag on to fabricate(), so
the steps avoided a stray ID column only because they
normally run with data already in hand, and a declaration that spelled
out handler = fabricate got the ID anyway. The
rule now belongs to the verb, whichever handler is named.mean_estimand, as
in 1.x; the join had dropped it.ATE, with other inquiries declared beside it,
produce more rows than either table had, because the unanswered
inquiries keep their own rows; the old test was that row count alone, so
it reported a multiplication that had not happened and advised naming an
inquiry the estimators had already named. A shared-column match now
warns only where one key value carries more than one row on both sides,
and says which key. A match on no shared column warns as before.declare_sampling(handler = ) takes a custom sampling
function, as the other data verbs do.S column and has no
filter warns once that every row was kept.redesign() names the list it returns by the values that
distinguish each design (closes #472).
redesign(design, N = c(10, 20)) gives N = 10
and N = 20, so a simulation’s design column
and bind_rows(.id = "design") carry the values that vary;
1.x named them design_1, design_2, which is
what a reader already knew from the position. A parameter whose value
cannot be written down, such as a function or a data frame, leaves the
whole list positional.These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.