Tools for testing and improving accuracy of statistical results.


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Documentation for package ‘accuracy’ version 1.35

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anova.sensitivity Generic methods for perturbations.
chisqtst Benchmark data to test the accuracy of statistical distribution functions, function to compute log relative error
dehaan dehaan global optimality test
firstLook Take a first look at a dataset
frexp Function to convert vector of floating-point numbers to fractional and integral components
ftst Benchmark data to test the accuracy of statistical distribution functions, function to compute log relative error
gammatst Benchmark data to test the accuracy of statistical distribution functions, function to compute log relative error
HTML.sensitivity.anova HTML methods for perturbation analysis
HTML.sensitivity.sim.summary HTML methods for perturbation analysis
HTML.sensitivity.summary HTML methods for perturbation analysis
LRE Functions for comparing results: LRE, compare, agrees
modelBetas Functions for comparing results: LRE, compare, agrees
modelsAgree Functions for comparing results: LRE, compare, agrees
modelsCompare Functions for comparing results: LRE, compare, agrees
modelSummary Functions for comparing results: LRE, compare, agrees
normtst Benchmark data to test the accuracy of statistical distribution functions, function to compute log relative error
perturb Data Perturbations based Sensitivity Analysis
plot.accFirstLook Generic methods for first look.
plot.sensitivity Generic methods for perturbations.
plot.sensitivity.summary Generic methods for perturbations.
print.accFirstLook Generic methods for first look.
print.sensitivity Generic methods for perturbations.
psim perform zelig simulations for perturbed models
PTBdefault Returns a default perturbation function for a given vector.
PTBdefaultfn Returns a default perturbation function for a given vector.
PTBdiscrete Function to perturb vectors of discrete numeric values or factors, logicals, characters
PTBi functions to add random noise to a vector
PTBmn.gen generator functions for multiple rounds of noise
PTBms functions to add random noise to a vector
PTBmsb functions to add random noise to a vector
PTBmsbr functions to add random noise to a vector
PTBmu.gen generator functions for multiple rounds of noise
PTBn functions to add random noise to a vector
PTBnbr functions to add random noise to a vector
PTBnbrr functions to add random noise to a vector
PTBnc functions to add random noise to a vector
PTBns functions to add random noise to a vector
PTBnsbr functions to add random noise to a vector
PTBnsbrr functions to add random noise to a vector
PTBu functions to add random noise to a vector
PTBubr functions to add random noise to a vector
PTBubrr functions to add random noise to a vector
PTBuc functions to add random noise to a vector
PTBus functions to add random noise to a vector
PTBusbr functions to add random noise to a vector
PTBusbrr functions to add random noise to a vector
pzelig Perturbations-based Sensitivity Analysis of Zelig Models
reclass.mat.diag Function to produce reclassification matrices
reclass.mat.random Function to produce reclassification matrices
resetSeed Function to return TRUE (not pseudo) random numbers, based on system and networked entropy collection.
rnormS Function to return TRUE (not pseudo) random numbers, based on system and networked entropy collection.
rstarMix Function to return TRUE (not pseudo) random numbers, based on system and networked entropy collection.
runifS Function to return TRUE (not pseudo) random numbers, based on system and networked entropy collection.
runifT Function to return TRUE (not pseudo) random numbers, based on system and networked entropy collection.
sechol Schnabel-Eskow Choleksy Decomposition
sensitivity Data Perturbations based Sensitivity Analysis
sensitivityZelig Perturbations-based Sensitivity Analysis of Zelig Models
setx.sensitivity perform zelig simulations for perturbed models
starr staff global optimum test
summary.sensitivity Generic methods for perturbations.
trueRandom Function to return TRUE (not pseudo) random numbers, based on system and networked entropy collection.
ttst Benchmark data to test the accuracy of statistical distribution functions, function to compute log relative error