Jackknife is a resampling technique that is used to estimate the bias and other statistical properties of an estimator. Here is how you can perform Jackknife on an array in matlab:
main.m328 chars15 lines
In the above code, we first create an example array arr
. Then we perform jackknife by looping over each element of the array and leaving it out of the analysis. For each iteration, we calculate the statistic of interest, in this case, the mean of the remaining elements in the array. We save these statistics in the jstat
vector. Finally, we calculate the Jackknife bias by averaging the statistic estimates and subtracting the overall mean from this average.
Note that this example code is assuming that the estimator of interest is the mean. In practice, this estimator could be any function of the data.
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