From biased coin to any discrete distribution

Tossing a Biased Coin

When we talk about a coin toss, we think of it as unbiased: with probability one-half it comes up heads, and with probability one-half it comes up tails. An ideal unbiased coin might not correctly model a real coin, which could be biased slightly one way or another. After all, real life is rarely fair. This possibility leads us to an interesting mathematical and computational question. Is there...

The distribution of loss in two-treatment biased-coin designs.

The paper compares randomized rules of the biased-coin type for the sequential allocation of treatments in a clinical trial. An important characteristic is the loss, which measures the increase in the variance of parameter estimates due to the imbalance caused by randomization. Simulations are used to find the small-sample distribution of loss. For some rules a simple chi-squared approximation ...

UNBIASED COIN TOSSING WITH A BIASED COIN by

PrQcedures are exhibited and analyzed for converting a sequence of iid Bernoulli variables with unknown mean p into a Bernoulli variable with mean 1/2. The efficiency of several procedures is studied.

Generic yet Practical ZK Arguments from any Public-Coin HVZK

In this work, we present a generic yet practical transformation from any public-coin honest-verifier zero-knowledge (HVZK) protocols to normal zero-knowledge (ZK) arguments. By “generic”, we mean that the transformation is applicable to any public-coin HVZK protocol under any one-way function (OWF) admitting Σ-protocols. By “practical” we mean that the transformation does not go through general...

Ecient Simulations by a Biased Coin