| Name : R-conf
| |
| Version : 1.9.1
| Vendor : obs://build_opensuse_org/devel:languages:R
|
| Release : lp154.3.1
| Date : 2024-07-13 15:03:57
|
| Group : Development/Libraries/Other
| Source RPM : R-conf-1.9.1-lp154.3.1.src.rpm
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| Size : 3.19 MB
| |
| Packager : https://www_suse_com/
| |
| Summary : Visualization and Analysis of Statistical Measures of Confidence
|
Description :
Enables: (1) plotting two-dimensional confidence regions, (2) coverage
analysis of confidence region simulations, (3) calculating confidence
intervals and the associated actual coverage for binomial proportions,
(4) calculating the support values and the probability mass function of
the Kaplan-Meier product-limit estimator, and (5) plotting the actual
coverage function associated with a confidence interval for the
survivor function from a randomly right-censored data set. Each is
given in greater detail next. (1) Plots the two-dimensional confidence
region for probability distribution parameters (supported distribution
suffixes: cauchy, gamma, invgauss, logis, llogis, lnorm, norm, unif,
weibull) corresponding to a user-given complete or right-censored
dataset and level of significance. The crplot() algorithm plots more
points in areas of greater curvature to ensure a smooth appearance
throughout the confidence region boundary. An alternative heuristic
plots a specified number of points at roughly uniform intervals along
its boundary. Both heuristics build upon the radial profile
log-likelihood ratio technique for plotting confidence regions given by
Jaeger (2016) < doi:10.1080/00031305.2016.1182946>, and are detailed in
a publication by Weld et al. (2019)
< doi:10.1080/00031305.2018.1564696>. (2) Performs confidence region
coverage simulations for a random sample drawn from a user- specified
parametric population distribution, or for a user-specified dataset and
point of interest with coversim(). (3) Calculates confidence interval
bounds for a binomial proportion with binomTest(), calculates the
actual coverage with binomTestCoverage(), and plots the actual coverage
with binomTestCoveragePlot(). Calculates confidence interval bounds for
the binomial proportion using an ensemble of constituent confidence
intervals with binomTestEnsemble(). Calculates confidence interval
bounds for the binomial proportion using a complete enumeration of all
possible transitions from one actual coverage acceptance curve to
another which minimizes the root mean square error for n < = 15 and
follows the transitions for well-known confidence intervals for n > 15
using binomTestMSE(). (4) The km.support() function calculates the
support values of the Kaplan-Meier product-limit estimator for a given
sample size n using an induction algorithm described in Qin et al.
(2023) < doi:10.1080/00031305.2022.2070279>. The km.outcomes() function
generates a matrix containing all possible outcomes (all possible
sequences of failure times and right-censoring times) of the value of
the Kaplan-Meier product-limit estimator for a particular sample size
n. The km.pmf() function generates the probability mass function for
the support values of the Kaplan-Meier product-limit estimator for a
particular sample size n, probability of observing a failure h at the
time of interest expressed as the cumulative probability percentile
associated with X = min(T, C), where T is the failure time and C is the
censoring time under a random-censoring scheme. The km.surv() function
generates multiple probability mass functions of the Kaplan-Meier
product-limit estimator for the same arguments as those given for
km.pmf(). (5) The km.coverage() function plots the actual coverage
function associated with a confidence interval for the survivor
function from a randomly right-censored data set for one or more of the
following confidence intervals: Greenwood, log-minus-log, Peto,
arcsine, and exponential Greenwood. The actual coverage function is
plotted for a small number of items on test, stated coverage, failure
rate, and censoring rate. The km.coverage() function can print an
optional table containing all possible failure/censoring orderings,
along with their contribution to the actual coverage function.
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RPM found in directory: /packages/linux-pbone/ftp5.gwdg.de/pub/opensuse/repositories/devel:/languages:/R:/autoCRAN/15.4/x86_64 |
