Tools for testing and improving accuracy of statistical results.

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Documentation for package `accuracy' version 1.04

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chisqtst Benchmark data to test the accuracy of statistical distribution functions, function to compute log relative error
dehaan Function to test that an optimum from MLE, NLS, or other non-linear optization routine is a global optimum
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
initPool Function to return TRUE (not pseudo) random numbers, based on system and networked entropy collection.
LRE Benchmark data to test the accuracy of statistical distribution functions, function to compute log relative error
normtst Benchmark data to test the accuracy of statistical distribution functions, function to compute log relative error
perturb Data Perturbations based Sensitivity Analysis
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
resetSeed 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
starr Function to test that an optimum from MLE, NLS, or other non-linear optization routine is a global optimum
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