Category: non-parametric statistics

• Calculating Derivatives from Random Forests

  bridge to somewhere . Calculus . dependent data . dynamic generalized linear models . dynamical systems . ensemble methods . ensemble models . filtering . forecasting . hierarchical clustering . linear regression . model-free forecasting . Monte Carlo Statistical Methods . non-mechanistic modeling . non-parametric model . non-parametric statistics . numerical algorithms . prediction . R statistical programming language . random forests . regression . sampling . splines . statistical learning . statistical series . statistics . time derivatives . time series

  Jun 27.2020
• Simplistic and Dangerous Models

  Generalized Additive Models . non-parametric statistics . science . statistics

  Apr 27.2020
• Reanalysis of business visits from deployments of a mobile phone app

  Bayesian computational methods . biology . capture-mark-recapture . capture-recapture . Christian Robert . count data regression . cumulants . diffusion . diffusion processes . Ecological Society of America . ecology . epidemiology . experimental science . field research . Gibbs Sampling . Internet measurement . Jean-Michel Marin . linear regression . mark-recapture . mathematics . maximum likelihood . Monte Carlo Statistical Methods . multilist methods . multivariate statistics . non-mechanistic modeling . non-parametric statistics . numerics . open source scientific software . Pierre-Simon Laplace . population biology . population dynamics . quantitative biology . quantitative ecology . R . R statistical programming language . sampling . sampling algorithms . segmented package in R . statistical ecology . statistical models . statistical regression . statistical series . statistics . stepwise approximation . stochastic algorithms . surveys . V. M. R. Muggeo

  Feb 20.2020
• Procrustes tangent distance is better than SNCD

  data science . dependent data . descriptive statistics . divergence measures . hydrology . Ian Dryden . information theoretic statistics . J.T.Kent . Kanti Mardia . non-parametric statistics . normalized compression divergence . quantitative ecology . R statistical programming language . spatial statistics . statistical series . time series

  Feb 24.2019
• Stream flow and P-splines: Using built-in estimates for smoothing

  American Statistical Association . citizen data . citizen science . Clausius-Clapeyron equation . Commonwealth of Massachusetts . cross-validation . data science . dependent data . descriptive statistics . dynamic linear models . empirical likelihood . environment . flooding . floods . Grant Foster . hydrology . likelihood-free . meteorological models . model-free forecasting . non-mechanistic modeling . non-parametric . non-parametric model . non-parametric statistics . numerical algorithms . precipitation . quantitative ecology . statistical dependence . statistical series . stream flow . Tamino . the bootstrap . time series . water vapor

  Jan 28.2019
• Series, symmetrized Normalized Compressed Divergences and their logit transforms

  Akaike Information Criterion . bridge to somewhere . computation . content-free inference . data science . descriptive statistics . divergence measures . engineering . George Sughihara . information theoretic statistics . likelihood-free . machine learning . mathematics . model comparison . model-free forecasting . multivariate statistics . non-mechanistic modeling . non-parametric statistics . numerical algorithms . statistics . theoretical physics . thermodynamics . time series

  Jan 3.2019