Satellite precipitation products (SPPs) provide alternative precipitation data for regions with sparse rain gauge measurements. However, SPPs are subject to different types of error that need correction. Most SPP bias correction methods use the statistical properties of the rain gauge data to adjust the corresponding SPP data. The statistical adjustment does not make it possible to correct the ...

Projections of Arctic sea ice thickness (SIT) have the potential to inform stakeholders about accessibility to the region, but are currently rather uncertain. The latest suite of CMIP5 global climate models (GCMs) produce a wide range of simulated SIT in the historical period (1979–2014) and exhibit various biases when compared with the Pan-Arctic Ice–Ocean Modelling and Assimilation System (PI...

Presence-only data, where information is available concerning species presence but not species absence, are subject to bias due to observers being more likely to visit and record sightings at some locations than others (hereafter "observer bias"). In this paper, we describe and evaluate a model-based approach to accounting for observer bias directly--by modelling presence locations as a functio...

MAXENT is now a common species distribution modeling (SDM) tool used by conservation practitioners for predicting the distribution of a species from a set of records and environmental predictors. However, datasets of species occurrence used to train the model are often biased in the geographical space because of unequal sampling effort across the study area. This bias may be a source of strong ...

Bagging an estimator approximately doubles its bias through the impact of bagging on quadratic terms in expansions of the estimator. This difficulty can be alleviated by bagging a suitably bias-corrected estimator, however. In these and other circumstances, what is the overall impact of bagging and/or bias correction, and how can it be characterised? We answer these questions in the case of gen...

We present a new derivation of the asymptotic correction for bias in the estimate of information from a finite sample. The new derivation reveals a relationship between information estimates and a sequence of polynomials with combinatorial significance, the exponential (Bell) polynomials, and helps to provide an understanding of the form and behavior of the asymptotic correction for bias.

The coherence between oscillatory activity in local field potentials (LFPs) and single neuron action potentials, or spikes, has been suggested as a neural substrate for the representation of information. The power spectrum of a spike-triggered average (STA) is commonly used to estimate spike field coherence (SFC). However, when a finite number of spikes is used to construct the STA, the coheren...

It is well known that output from climate models cannot be used to force hydrological simulations without some form of preprocessing to remove the existing biases. In principle, statistical bias correction methodologies act on model output so the statistical properties of the corrected data match those of the observations. However, the improvements to the statistical properties of the data are ...

25 The coherence between oscillatory activity in local field potentials (LFP) and single neuron action 26 potentials, or spikes, has been suggested as a neural substrate for the representation of information. 27 The power spectrum of a spike triggered average (STA) is commonly used to estimate spike field 28 coherence (SFC). However, when a finite number of spikes are used to construct the STA,...