Exact testing with random permutations

When permutation methods are used in practice, often a limited number of random permutations are used to decrease the computational burden. However, most theoretical literature assumes that the whole permutation group is used, and methods based on random permutations tend to be seen as approximate. There exists a very limited amount of literature on exact testing with random permutations and only recently a thorough proof of exactness was given. In this paper we provide an alternative proof, viewing the test as a "conditional Monte Carlo test" as it has been called in the literature. We also provide extensions of the result. Importantly, our results can be used to prove properties of various multiple testing procedures based on random permutations

A simulation model for the functional response of Orius sauteri on eggplant leaves with Thrips palmi: Implications for biological control.

The predation capability of the anthocorid predatory bug Orius sauteri (Poppius) determines its effectiveness for suppressing Thrips palmi Karny on greenhouse eggplants. For quantifying the daily impact of one predator on its prey, we use its patch leaving behaviour on eggplant leaves with different prey numbers and scale up to the larger spatiotemporal scale of the greenhouse and one foraging day, using literature data on the distribution of T. palmi over eggplant leaves. The simulation result is a type-II functional response of O. sauteri as function of average T. palmi density: around the economic injury level of T. palmi, i.e., 0.55 individuals per leaf, O. sauteri can find and eat approximately 10 prey per day. The sensitivity analysis showed that the baseline leaving tendency, the presence of and the encounter rate with prey have a relatively large effect on the daily mean number of prey eaten per O. sauteri predator, i.e., its predation capability

Stochastic dynamic simulation of fruit abortion: a case study of sweet pepper

Abortion of reproductive organs diminishes yields in many crops. In indeterminate greenhouse crops, alternating periods of fruit abortion and fruit set exist, resulting in fluctuations in fruit yield. Factors affecting the level of abortion are e.g., the supply and demand for assimilates (source and sink strength, respectively), temperature and cultivar. However, simulation of fruit abortion is still a weak part of crop simulation models. Variation in fruit abortion exists between plants, which results in differences in the timing and the number of set fruits. Therefore, simulating fruit abortion with variation could give more realistic simulation results. The probability of a fruit to abort should be related to factors like source strength and sink strength. The more favourable the circumstances are for fruit abortion, e.g., low source strength or high sink strength, the more likely it is that the fruit aborts. Survival analysis estimates parameters quantifying the influence of explanatory variables on the abortion rate. Time-varying explanatory variables can be used in the analysis. In a case study, we used survival analysis to analyse a data set with observations on flowering, fruit abortion and fruit harvest for sweet pepper. Source and sink strength were used as explanatory variables. The resulting equation determining the probability of abortion per day was implemented in a simple simulation model to simulate fruit set. The model output, as an average of 100 plants, showed similar timing in the fluctuations in fruit set as the observations, although the amplitude of the fluctuations was in some cases underestimated. The percentage fruit set was simulated correctl

On the term "randomization test"

There exists no consensus on the meaning of the term "randomization test". Contradicting uses of the term are leading to confusion, misunderstandings and indeed invalid data analyses. As we point out, a main source of the confusion is that the term was not explicitly defined when it was first used in the 1930's. Later authors made clear proposals to reach a consensus regarding the term. This resulted in some level of agreement around the 1970's. However, in the last few decades, the term has often been used in ways that contradict these proposals. This paper provides an overview of the history of the term per se, for the first time tracing it back to 1937. This will hopefully lead to more agreement on terminology and less confusion on the related fundamental concepts