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Jackknife variance estimates for random forest

In statistics, jackknife variance estimates for random forest are a way to estimate the variance in random forest models, in order to eliminate the… Expand
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Bootstrapping (statistics)Random forest

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2018
2018
Empirical Influence Functions of Hodges-Lehmann Weighted Estimates Applied in Deformation Analysis
The paper concerns the empirical influence functions of the Hodges-Lehmann weighted estimates (HLWE) of the shift. These… Expand
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2015
2015
The Numerical Analysis of KL Quantile Estimates
Abstract: This article uses R software KL quantile estimate numerical simulation under different distributions and different… Expand
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2010
2010
Selection between models through multi-step-ahead forecasting
We develop and show applications of two new test statistics for deciding if one ARIMA model provides significantly better h-step… Expand
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2005
2005
Improving Estimates of Nitrate Leaching for Quantifying New Zealand’s Indirect Nitrous Oxide Emissions
New Zealand’s indirect nitrous oxide (N2O) emissions have been estimated to contribute approximately 23% of the national nitrous… Expand
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