machine learning - Are there any contemporary uses of jackknifing ...
General model assessment is usually done using cross-validation and ROC curves. However, she is using the output of the model to derive a single numeric description of the model output and would like a confidence interval around that number; Jackknifing appears to be a reasonable way to characterize uncertainty around this value.
Randomization/permutation tests - Cross Validated
Resampling methods are used in (1) estimating precision / accuracy of sample statistics through using subset of data (e.g. Jackknifing) or drawing randomly with replacement from a set of data points (e.g. bootstrapping) (2) Exchanging labels on data points when performing significance tests (permutation tests, also called exact tests ...
r - Bootstrap vs. jackknife - Cross Validated
2019年2月20日 · Jackknifing is much older (perhaps ~20 years); it's main advantage in the days when computing power was limited, was that it's computationally much simpler. However, the bootstrap provides information about the whole sampling distribution, and …
cross validation - Jackknife vs. LOOCV - Cross Validated
2015年3月30日 · In cross-validation you compute a statistic on the left-out sample(s). Most often, you predict the left-out sample(s) by a model built on the kept samples. In jackknifing, you compute a statistic from the kept samples only.
jackknifing blocks (*not* time series) - Cross Validated
2015年2月18日 · Please let me know what you think of this idea: do a jackknife, but instead of computing s() for x[-i], i=1 to 50 (where -i means delete observation x[i]) in the usual jackknifing way, instead compute s() deleting each subject. Then get the SD estimate the usual way.
What is the difference between jackknifing and LOOCV?
Leave-one-out cross-validation model technique is very similar to jackknifing resampling, because both omitting each training case and perform retraining of the network on the left-out subset. On wiki page we can read that jackknifing computes a statistic from the kept samples only, while LOOCV computes a statistic on the left-out sample(s).
Comparison of the jacknife vs the bootstrap - Cross Validated
$\begingroup$ Do a Google search with key words Efron jackknife bootstrap resampling. That is how I found it. The link will show up at the top of the list There is a wealth of information on this topic that you can look for on the net.
Jackknifing for assessing the "robustness" of test results
2021年2月8日 · In a presentation I saw recently, a two-sided t-test was repeated with jackknifed subsets of the original data in order to assess the result's "robustness". In detail, they took a random ...
Best suggested textbooks on Bootstrap resampling?
2014年12月12日 · It might be worth going back to the origins of Bootstrapping and learning a bit about jackknifing from sources such as Quenouille and Tukey. Personally, the book "Data analysis and regression : a second course in statistics" by Mosteller and Tukey really helped me when I was first learning about bootstrapping.
Estimating the total with jackknife - Cross Validated
At a homework assignment, we are supposed to estimate the total in a population using a Horvitz Thompson estimator, and then estimate the variance using the jackknife technique. As a first step, I