From MFKP_wiki

Jump to: navigation, search

Selection: with tag resampling [7 articles] 


Statistical modeling: the two cultures (with comments and a rejoinder by the author)

Statistical Science, Vol. 16, No. 3. (August 2001), pp. 199-231,


There are two cultures in the use of statistical modeling to reach conclusions from data. One assumes that the data are generated by a given stochastic data model. The other uses algorithmic models and treats the data mechanism as unknown. The statistical community has been committed to the almost exclusive use of data models. This commitment has led to irrelevant theory, questionable conclusions, and has kept statisticians from working on a large range of interesting current problems. Algorithmic modeling, both in ...


An empirical comparison of model validation techniques for defect prediction models

IEEE Transactions on Software Engineering, Vol. 43, No. 1. (1 January 2017), pp. 1-18,


Defect prediction models help software quality assurance teams to allocate their limited resources to the most defect-prone modules. Model validation techniques, such as k -fold cross-validation, use historical data to estimate how well a model will perform in the future. However, little is known about how accurate the estimates of model validation techniques tend to be. In this paper, we investigate the bias and variance of model validation techniques in the domain of defect prediction. Analysis of 101 public defect datasets ...


Resampling methods for meta-model validation with recommendations for evolutionary computation

Evolutionary Computation, Vol. 20, No. 2. (16 February 2012), pp. 249-275,


Meta-modeling has become a crucial tool in solving expensive optimization problems. Much of the work in the past has focused on finding a good regression method to model the fitness function. Examples include classical linear regression, splines, neural networks, Kriging and support vector regression. This paper specifically draws attention to the fact that assessing model accuracy is a crucial aspect in the meta-modeling framework. Resampling strategies such as cross-validation, subsampling, bootstrapping, and nested resampling are prominent methods for model validation and ...


Evaluation of optical remote sensing to estimate actual evapotranspiration and canopy conductance

Remote Sensing of Environment, Vol. 129 (February 2013), pp. 250-261,


[Abstract] We compared estimates of actual evapotranspiration (ET) produced with six different vegetation measures derived from the MODerate resolution Imaging Spectroradiometer (MODIS) and three contrasting estimation approaches using measurements from eddy covariance flux towers at 16 FLUXNET sites located over six different land cover types. The aim was to assess optimal approaches in using optical remote sensing to estimate ET. The first two approaches directly regressed various MODIS vegetation indices (VIs) and products such as leaf area index (LAI) and fraction of ...


(INRMM-MiD internal record) List of keywords of the INRMM meta-information database - part 34

(February 2014)
Keywords: inrmm-list-of-tags   record-to-update-or-delete   recreation   red-list   redd   redistributable-scientific-information   reference-manual   reforestation   refugia   regeneration   regime-shift   regional-climate   regional-climate-models   regional-scale   regression   regression-tree-analysis   regulating-services   reinforcement   reinforcement-learning   reinventing-weels   reiteration   relative-distance-similarity   relative-distance-similarity-ancillary   remote-sensing   renewable-energy   renewable-energy-directive   repeatability   repellent-species   replicability   reporting   representative-concentration-pathways   reproducibility   reproducible-research   reproduction   reproductive-effort   reptiles   resampling   research-funding   research-funding-vs-public-outcome   research-management   research-metrics   research-team-size   reservoir-management   reservoir-services   resilience   resilience-vs-resistance   resilience-vs-risk-management   resin   resistance   resources-exploitation   respiration   restoration   resurvey-of-semi-permanent   retraction   review   review-publication   review-scopus-european-biodiversity-indicators   revision-control-system   rewarding-best-research-practices   rhamnus-cathartica   rhamnus-catharticus   rhamnus-frangula   rhamnus-imeretina   rhamnus-saxatilis   rhamnus-spp   rhizophagus-grandis   rhizophora-apiculata   rhizophora-mangle   rhododendron-arboreum   rhododendron-caucasicum   rhododendron-ferrugineum   rhododendron-periclymenoides   rhododendron-ponticum   rhododendron-smirnowii   rhododendron-spp   rhododendron-ungernii   rhododendron-viscosum   rhopalicus-tutela   rhus-spp   rhus-typhina   rhyacionia-bouliana   rhyacionia-buoliana   rhyacionia-frustrana   rhynchophorus-ferrugineus   rhyssa-persuasoria   rhytisma   ribes-alpinum   ribes-rubrum   ribes-uva-crispa   rice   ring-analysis   ring-width-chronologies   ringspot-virus   riparian-ecosystem   riparian-forest   riparian-zones   risk-analysis   risk-assessment   risk-management   risk-reduction  


List of indexed keywords within the transdisciplinary set of domains which relate to the Integrated Natural Resources Modelling and Management (INRMM). In particular, the list of keywords maps the semantic tags in the INRMM Meta-information Database (INRMM-MiD). [\n] The INRMM-MiD records providing this list are accessible by the special tag: inrmm-list-of-tags ( ). ...


The reusable holdout: preserving validity in adaptive data analysis

Science, Vol. 349, No. 6248. (07 August 2015), pp. 636-638,


[Editor's summary: Testing hypotheses privately] Large data sets offer a vast scope for testing already-formulated ideas and exploring new ones. Unfortunately, researchers who attempt to do both on the same data set run the risk of making false discoveries, even when testing and exploration are carried out on distinct subsets of data. Based on ideas drawn from differential privacy, Dwork et al. now provide a theoretical solution. Ideas are tested against aggregate information, whereas individual data set components remain confidential. Preserving that ...


Bootstrap tests: how many bootstraps?

Econometric Reviews, Vol. 19, No. 1. (1 January 2000), pp. 55-68,


In practice, bootstrap tests must use a finite number of bootstrap samples. This means that the outcome of the test will depend on the sequence of random numbers used to generate the bootstrap samples, and it necessarily results in some loss of power. We examine the extent of this power loss and propose a simple pretest procedure for choosing the number of bootstrap samples so as to minimize experimental randomness. Simulation experiments suggest that this procedure will work very well in ...

This page of the database may be cited as:
Integrated Natural Resources Modelling and Management - Meta-information Database.

Publication metadata

Bibtex, RIS, RSS/XML feed, Json, Dublin Core

Meta-information Database (INRMM-MiD).
This database integrates a dedicated meta-information database in CiteULike (the CiteULike INRMM Group) with the meta-information available in Google Scholar, CrossRef and DataCite. The Altmetric database with Article-Level Metrics is also harvested. Part of the provided semantic content (machine-readable) is made even human-readable thanks to the DCMI Dublin Core viewer. Digital preservation of the meta-information indexed within the INRMM-MiD publication records is implemented thanks to the Internet Archive.
The library of INRMM related pubblications may be quickly accessed with the following links.
Search within the whole INRMM meta-information database:
Search only within the INRMM-MiD publication records:
Full-text and abstracts of the publications indexed by the INRMM meta-information database are copyrighted by the respective publishers/authors. They are subject to all applicable copyright protection. The conditions of use of each indexed publication is defined by its copyright owner. Please, be aware that the indexed meta-information entirely relies on voluntary work and constitutes a quite incomplete and not homogeneous work-in-progress.
INRMM-MiD was experimentally established by the Maieutike Research Initiative in 2008 and then improved with the help of several volunteers (with a major technical upgrade in 2011). This new integrated interface is operational since 2014.