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Conditional tests are constructed by conditioning a fit measure to a minimal sufficient statistic. To calculate the p-value of these tests, Monte Carlo methods with co-sufficient samples can be used. In this paper we show how to simulate co-sufficient samples when the data distribution belongs to the exponential family with doubly transitive sufficient statistics. The proposed method is illustrated using the beta distribution. [ABSTRACT FROM AUTHOR]

There are several arthropods that can transmit disease to humans. To make inferences about the rate of infection of these arthropods, it is common to collect a large sample of vectors, divide them into groups (called pools), and apply a test to detect infection. This paper presents an approximate likelihood point estimator to rate of infection for pools of different sizes, when the variability of these sizes is small and the infection rate is low. The performance of this estimator was evaluated in four simulated scenarios, created from real experiments selected in the literature. The new estimator performed well in three of these scenarios. As expected, the new estimator performed poorly in the scenario with great variability in the size of the pools for some values of the parameter space. [ABSTRACT FROM AUTHOR]