Nothing
delta_n
with exposure range.include_details = TRUE
.
*generate_pseudo_pop
does not take Y
as an input. generate_syn_data
supports vectorized_y
to accelerate data generation.matching_fun
--> dist_measure
matching_l1
--> matching_fn
estimate_semipmetric_erf
now takes the gam
models optional arguments.estimate_pmetric_erf
now takes the gnm
models optional arguments.trim_quantiles
--> exposure_trim_qtls
generate_pseudo_pop
function accepts gps_obj
as an optional input.internal_use
is not part of parameters for estimate_gps
function. estimate_gps
function only returns id
, w
, and computed gps
as part of dataset.gps_model
--> gps_density
. Now it takes, normal
and kernel
options instead of parametric
and non-parametric
options.estimate_npmetric_erf
supports both locpol
and KernSmooth
approaches.gps_trim_qtls
input parameter to trim data samples based on gps values.stats::density
function. wCorr
release (#193).optimzied_compile == TRUE
.earth
package is part of suggested packages. estimate_npmetric_erf
assigns user-defined log file.estimate_npmetric_erf
:matched_Y
--> m_Y
matched_w
--> m_w
matched_cw
--> counter_weight
estimate_npmetric_erf
function, the matched_cw
input is now mandatory. locpol::locpol
function.earth
and ranger
are not installed automatically. They can be installed manually if needed.sysdata.rda
is modified to reflect transition from counter
and ipw
to counter_weight
counter_weight
is used as a counter or weight, in matching
or weighting
approaches. counter
and ipw
are dropped.sl_lib
becomes a required argument.gpsm_pspop
S3 object returns details of the adjusting process. Kolmogorov-Smirnov(KS)
statistics are provided for the computed pseudo population.effect size
for the generated pseudo population is computed and reported.pseodo_pop
also includes covariate column names.compute_closest_wgps_helper_no_sc
is added to take care of the mostly used special case (scale = 1).KernSmooth
and tidyr
packages. pred_model
argument dropped. The package only predicts using SuperLearner.estimate_gps
returns the optimal hyperparameters.estimate_gps
returns S3 object. verbose
parameter.set_logger
function.weighting
option as causal inference approach. param
as an argument to accept hyperparameters from users.m_xgboost
instead of SL.xgboost
to use XGBoost package for prediction purposes.mcSuperLearner
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