Robust bias correction model for estimation of global trend in marine populations
Sign Up to like & getrecommendations! Published in 2017 at "Ecosphere"
DOI: 10.1002/ecs2.2038
Abstract: In modeling biological and ecological processes from data, it is essential to deal with data selection bias properly in order to obtain reliable and reasonable predictions. To incorporate the mechanism of selection bias into a… read more here.
Keywords: estimation; model; bias correction; robust bias ... See more keywords
Non‐stationary bias correction of monthly CMIP5 temperature projections over China using a residual‐based bagging tree model
Sign Up to like & getrecommendations! Published in 2017 at "International Journal of Climatology"
DOI: 10.1002/joc.5188
Abstract: The biases in the Global Circulation Models (GCMs) are crucial for understanding future climate changes. Currently, most bias correction methodologies suffer from the assumption that model bias is stationary. This paper provides a non-stationary bias… read more here.
Keywords: bias correction; model; non stationary; temperature ... See more keywords
Regression‐based regionalization for bias correction of temperature and precipitation
Sign Up to like & getrecommendations! Published in 2019 at "International Journal of Climatology"
DOI: 10.1002/joc.6020
Abstract: Statistical bias correction methods are inferred relationships between inputs and outputs. The constructed functions are based on available observations, which are limited in time and space. This study investigates the ability of regression models (linear… read more here.
Keywords: temperature precipitation; bias correction; climatology; regression ... See more keywords
Limitations of univariate linear bias correction in yielding cross‐correlation between monthly precipitation and temperature
Sign Up to like & getrecommendations! Published in 2019 at "International Journal of Climatology"
DOI: 10.1002/joc.6086
Abstract: Statistical bias correction techniques are commonly used in climate model projections to reduce systematic biases. Among the several bias correction techniques, univariate linear bias correction (e.g., quantile mapping) is the most popular, given its simplicity.… read more here.
Keywords: cross correlation; bias correction; cross; univariate linear ... See more keywords
A novel bias correction method for extreme rainfall events based on L‐moments
Sign Up to like & getrecommendations! Published in 2021 at "International Journal of Climatology"
DOI: 10.1002/joc.7242
Abstract: The effectiveness of bias correction (BC) of global‐scale future climate projections is crucial in climate change studies. The magnitude of error in the BC affect climate change adaptation decisions. The existing BC methods vary in… read more here.
Keywords: rainfall events; method; day; bias correction ... See more keywords
Bias testing, bias correction, and confounder selection using an instrumental variable model.
Sign Up to like & getrecommendations! Published in 2020 at "Statistics in medicine"
DOI: 10.1002/sim.8730
Abstract: Instrumental variable (IV) analysis can be used to address bias due to unobserved confounding when estimating the causal effect of a treatment on an outcome of interest. However, if a proposed IV is correlated with… read more here.
Keywords: instrumental variable; ols estimator; bias correction; bias ... See more keywords
Projected precipitation changes over China for global warming levels at 1.5 °C and 2 °C in an ensemble of regional climate simulations: impact of bias correction methods
Sign Up to like & getrecommendations! Published in 2020 at "Climatic Change"
DOI: 10.1007/s10584-020-02841-z
Abstract: Four bias correction methods, i.e., gamma cumulative distribution function (GamCDF), quantile–quantile adjustment (QQadj), equidistant cumulative probability distribution function (CDF) matching (EDCDF), and transform CDF (CDF-t), to read are applied to five daily precipitation datasets over… read more here.
Keywords: precipitation; climate; correction; cdf ... See more keywords
Fast robust optimization using bias correction applied to the mean model
Sign Up to like & getrecommendations! Published in 2020 at "Computational Geosciences"
DOI: 10.1007/s10596-020-10017-y
Abstract: Ensemble methods are remarkably powerful for quantifying geological uncertainty. However, the use of the ensemble of reservoir models for robust optimization (RO) can be computationally demanding. The straightforward computation of the expected net present value… read more here.
Keywords: methodology; mean model; model; optimization ... See more keywords
Uncertainty analysis and ensemble bias-correction method for predicting nitrate leaching in tea garden soils
Sign Up to like & getrecommendations! Published in 2020 at "Agricultural Water Management"
DOI: 10.1016/j.agwat.2020.106182
Abstract: Abstract Pedotransfer functions were often applied to predict the soil water contents at field capacity (FC) and permanent wilting point (PWP), which are the key parameters used in the soil nitrogen (N) biogeochemical models for… read more here.
Keywords: bias correction; soil; prediction; uncertainty ... See more keywords
Forecast reconciliation: A geometric view with new insights on bias correction
Sign Up to like & getrecommendations! Published in 2021 at "International Journal of Forecasting"
DOI: 10.1016/j.ijforecast.2020.06.004
Abstract: Abstract A geometric interpretation is developed for so-called reconciliation methodologies used to forecast time series that adhere to known linear constraints. In particular, a general framework is established that nests many existing popular reconciliation methods… read more here.
Keywords: reconciliation geometric; reconciliation; forecast; bias correction ... See more keywords
A robust active contour model driven by pre-fitting bias correction and optimized fuzzy c-means algorithm for fast image segmentation
Sign Up to like & getrecommendations! Published in 2019 at "Neurocomputing"
DOI: 10.1016/j.neucom.2019.06.019
Abstract: Abstract Active contour model (ACM) is an effective method for image segmentation that has been widely used in various research fields. For images with severe intensity inhomogeneity, most existing ACMs show a poor segmentation performance.… read more here.
Keywords: active contour; model; bias correction; contour model ... See more keywords