High-Performance Open-Source Archive
rank_regression(): For all distributions, the
confidence intervals of the parameters are now computed on the basis of
a heteroscedasticity-consistent (HC) covariance matrix. If the
confidence intervals for the Weibull parameters are to be calculated
according to Mock, this must be specified via the new argument
options.mixmod_regression(): Since this function uses
rank_regression(), the changes regarding the confidence
intervals also apply here.plot_prob.wt_model(): Removed dysfunctional argument
distribution. The distribution is inferred using the model
x.delta_method(): Renamed argument p with
x.confint_betabinom() and confint_fisher():
Removed constant features distribution, bounds
and direction from the tibble output and added them as
attributes instead.mcs_mileage(): Changed name of output column
mileage to x (in accordance with
reliability_data()).mcs_delay(): Changed name of output column
time to x (in accordance with
reliability_data()).dist_mileage.default() (former
dist_mileage()): Renamed argument mileage with
x.mcs_mileage.default() (former
mcs_mileage()): Renamed argument mileage with
x.'exponential' and 'exponential2').estimate_cdf(): Added option
johnson_method to specify the formula which is used for
determining cumulative failure probabilities.rank_regression(): New arguments direction
(specifies direction of dependency in the model), control
(enables access to argument control in
optim()) and options (method used to calculate
the confidence intervals for the parameters, default is “HC”).r_squared_profiling(): New argument
direction.ml_estimation(): New arguments
start_dist_params (optional vector with initial values of
the parameters) and control (enables access to argument
control in optim()).loglik_profiling(): New argument wts.loglik_profiling() is now an S3 generic.
loglik_profiling() becomes
loglik_profiling.default(). Added
loglik_profiling.wt_reliability_data().loglik_function() is now an S3 generic.
loglik_function() becomes
loglik_function.default(). Added
loglik_function.wt_reliability_data().confint_betabinom(): Methods "kaplan" and
"nelson" of estimate_cdf() can be used for
beta-binomial confidence bounds.mcs_mileage_data(): Create consistent MCS data
for mcs_mileage().mcs_delay_data(): Create consistent MCS data for
mcs_delay().dist_mileage() is now an S3 generic.
dist_mileage() becomes dist_mileage.default().
Added dist_mileage.wt_mcs_mileage_data().dist_delay() is now an S3 generic.
dist_delay() becomes dist_delay.default().
Added dist_delay.wt_mcs_delay_data().dist_delay() now supports the estimation of multiple
delay distributions at once.mcs_mileage() is now an S3 generic.
mcs_mileage() becomes mcs_mileage.default().
Added mcs_mileage.wt_mcs_mileage_data().mcs_delay() is now an S3 generic.
mcs_delay() becomes mcs_delay.default(). Added
mcs_delay.wt_mcs_delay_data().print.wt_mcs_delay_data() and
print.wt_mcs_mileage_data().print.wt_mileage_estimation().print.wt_delay_estimation() for one delay and
print.wt_delay_estimation_list() for multiple delays.reliability_data(): Using !!
syntax with arguments x and status resulted in
an error.estimate_cdf() preserves additional columns, that were
returned from reliability_data(..., .keep_all = TRUE).print.wt_reliability_data().plot_conf(): Wrong confidence bounds were
displayed for direction = "x" (#181).plot_conf():
plot_method = "ggplot2" and exactly one method in
estimate_cdf() resulted in an error (#182).mcs_mileage() now has class
wt_mcs_mileage.mcs_delay() now has class
wt_mcs_delay.dist_mileage() now has class
wt_mileage_estimation.dist_delay() now has class
wt_delay_estimation or
wt_delay_estimation_list.plot_prob(): Better work out the distinction between
plot_prob.wt_cdf_estimation() and
plot_prob.wt_model(). The former is applied to a CDF
estimation whereas the latter is applied to a mixture model.mr_method(): Deprecated, use
estimate_cdf() instead. Renamed output column
characteristic with x. Set default value for
id to NULL.johnson_method(): Deprecated, use
estimate_cdf() instead. Renamed output column
characteristic with x. Set default value for
id to NULL.kaplan_method(): Deprecated, use
estimate_cdf() instead. Renamed output column
characteristic with x. Set default value for
id to NULL.nelson_method(): Deprecated, use
estimate_cdf() instead. Renamed output column
characteristic with x. Set default value for
id to NULL.plot_prob.default() (former plot_prob()):
Renamed event with status.plot_prob_mix(): Deprecated, use
plot_prob() instead. Removed default value
NULL for argument mix_output. Renamed
event with status.ml_estimation.default() (former
ml_estimation()): Renamed event with
status. Removed details. Changed names and
contents of list elements in output. See
?ml_estimation.loglik_function: Renamed event with
status. Renamed pars with
dist_params.rank_regression.default() (former
rank_regression()): Renamed event with
status. Removed details. Changed names and
contents of list elements in output. See
?rank_regression.mixmod_em.default() (former mixmod_em()):
Renamed event with status. Removed
post.mixmod_regression.default() (former
mixmod_regression()): Renamed event with
status. Added arguments k and
control, which provide finer control over the segmentation
process. Expect default setting to provide other results than in prior
versions.predict_prob(): Renamed loc_sc_params with
dist_params.predict_quantile(): Renamed loc_sc_params
with dist_params.plot_mod.default() (former plot_mod()):
Renamed event with status. Renamed
loc_sc_params with dist_params. Removed
y.plot_mod_mix(): Deprecated, use plot_mod()
instead. Renamed event with status.plot_pop(): Added argument tol to restrict
the range of failure probabilities. Removed argument color.
Renamed argument params to dist_params_tbl,
which only supports location and scale parameters (also for
distribution = "weibull"). Changed behavior of
dist_params_tbl: A tibble is now recommended
instead of a vector.confint_betabinom.default() (former
confint_betabinom()): Renamed event with
status. Renamed loc_sc_params with
dist_params. Added argument b_lives which
allows the user to specify probabilities p for
B_p-lives to be considered.confint_fisher.default() (former
confint_fisher()): Renamed event with
status. Renamed loc_sc_params with
dist_params. Renamed loc_sc_varcov with
dist_varcov. Added argument b_lives which
allows the user to specify probabilities p for
B_p-lives to be considered.delta_method(): Renamed loc_sc_params with
dist_params. Renamed loc_sc_varcov with
dist_varcov.plot_conf.default() (former plot_conf()):
Switched position of arguments direction and
distribution.dist_delay_register(): Deprecated, use
dist_delay() instead.dist_delay_report(): Deprecated, use
dist_delay() instead.mcs_delay_register(): Deprecated, use
mcs_delay() instead. Renamed x with
time. Renamed event with status.
Removed seed. Removed int_seed from output
list.mcs_delay_report(): Deprecated, use
mcs_delay() instead. Renamed x with
time. Renamed event with status.
Removed seed. Removed int_seed from output
list.mcs_delays(): Deprecated, use mcs_delay()
instead. Renamed x with time. Renamed
event with status. Removed seed.
Removed int_seed from output list.dist_mileage(): Removed event. Renamed
x with time. Switched position of arguments
time and mileage.mcs_mileage(): Removed event. Renamed
x with time. Switched position of arguments
time and mileage.plot_prob() or plot_pop() via
argument plot_method.reliability_data(): Create consistent reliability
data.estimate_cdf(): Unite functionality of
mr_method(), johnson_method(),
kaplan_method() and nelson_method(). Added
option ties.method for method = "mr", which
specifies how ties should be treated.estimate_cdf() and all
functions that depend on the cdf_estimation
(rank_regression(), plot_prob(),
plot_mod(), plot_conf(),
mixmod_regression()).plot_prob() and plot_mod() are able to
handle mixture models.mixmod_regression() is now more flexible. Argument
k can be used to control number of subgroups or to
determine them in an automatic fashion. Argument control
provides additional control over the segmentation procedure.print.wt_rank_regression(),
print.wt_ml_estimation(),
print.wt_model_estimation(),
print.wt_model_estimation_list(),
print.wt_mixmod_regression() and
print.wt_mixmod_regression_list().vcov.wt_model_estimation().dist_delay(): Generalizes the
distribution-specific modeling of delays.mcs_delay(): Generalizes the adjustment of
operating times by delays and supports multiple delays at once.rank_regression() is now an S3 generic.
rank_regression() becomes
rank_regression.default(). Added
rank_regression.wt_cdf_estimation().plot_prob() is now an S3 generic.
plot_prob() becomes plot_prob.default(). Added
plot_prob.wt_cdf_estimation() and
plot_prob.wt_model().plot_mod() is now an S3 generic.
plot_mod() becomes plot_mod.default(). Added
plot_mod.wt_model().plot_conf() is now an S3 generic.
plot_conf() becomes plot_conf.default(). Added
plot_conf.wt_confint().plot_pop(): Added support for multiple population lines
and comparison of two- and three-parametric distributions.dist_delay_register() and
dist_delay_report(): Use dist_delay()
instead.mcs_delay_register(), mcs_delay_report()
and mcs_delays(): Use mcs_delay()
instead.mr_method(), johnson_method(),
kaplan_method() and nelson_method(): Use
estimate_cdf() instead.plot_prob_mix(): Use plot_prob()
instead.plot_mod_mix(): Use plot_mod()
instead.calculate_ranks.mixture_em_cpp.plot_layout.plot_mod_mix() for the case of no
mixture distribution.confint_betabinom(): many cases near
one -> unique().mr_method(): assigning a rank for the
same lifetime.mixmod_regression: call to
segmented::segmented.lm() was incorrect."scatter" and scatter mode
"markers" to plotly plots.delta_method(), r_squared_profiling() and
loglik_profiling() were vectorized.plot_prob_mix() and
plot_mod_mix() is deprecated and not used anymore.plot_prob_mix() and plot_mod_mix() is
deprecated; use mix_output instead.plot_mod_mix() was revised and updated in the
way that the obtained results of the function mixmod_em()
can be visualized.plot_prob_mix() was revised and updated in the
way that the obtained results of the function mixmod_em()
can be visualized.mixture_em_cpp()) and is called in
mixmod_em().delta_method() and
confint_fisher() was made.loglik_profiling(). In
general this function is used inside ml_estimation() for
the purpose of estimating threshold parameter of three-parametric
models.r_squared_profiling(). In general this
function is used inside rank_regression() for the purpose
of estimating threshold parameter of three-parametric models.loglik_function(). In
general this function is used inside ml_estimation() for
the purpose of estimating the variance-covariance matrix of
location-scale models “sev”, “normal” and “logistic”. The function is
also used to estimate the variance-covariance matrix of
log-location-scale models with a threshold parameter, i.e. “weibull3”,
“lognormal3” and “loglogistic3”.ml_estimation():
wts for case weights.
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