Resampling Methods
Resampling methods are a set of techniques used to repeat data sampling – they simply rearrange the data to estimate the accuracy of a statistic. If we are developing a simulation model and we get unsatisfactory results, we can try to reorganize the starting data to remove any wrong correlations and re-check the capabilities of the model. Resampling methods are one of the most interesting inferential applications of stochastic simulations and random numbers. They are particularly useful in the nonparametric field, where the traditional inference methods cannot be correctly applied. They generate random numbers to be assigned to random variables or random samples. They require machine time related to the growth of repeated operations. They are very simple to implement and once implemented, they are automatic. The required elements must be placed in a sample that is, or at least can be, representative of the population. To achieve this, all the characteristics...
