In the case of EVs, some studies emphasize the buyer's lack of knowledge with the technology as a potential factor for the low demand [32]. However, sellers can decrease the information asymmetry by providing information about product attributes [102], whereas buyers can decrease the information...
In machine learning, the bias-variance trade-off is a fundamental concept affecting the performance of any predictive model. It refers to the delicate balance between bias error and variance error of a model, as it is impossible to simultaneously minimize both. Striking the right balance is cruci...
Randomization is an important tool used to establish causal inferences in studies designed to further our understanding of questions related to obesity and nutrition. To take advantage of the inferences afforded by randomization, scientific standards mus
Reddy, "The error in variables (EIV) regression approach as a means of identifying unbiased physical parameter estimates: Application to chiller performance data", International Journal of Heating, Ventilating, Air Conditioning and Refrigerating Research, 2002, 8(3):295-309...
Nevertheless, false absence data can introduce substantial bias to SDMs, leading to poor performance when fitting models (Gibson et al., 2007). Therefore, it is necessary to evaluate the degree to which false absence data can impact the accuracy of habitat suitability assessments. The Bohai Sea ...
A worst-case identification method in frequency domain is proposed to cope with the identification of errors-in-variables models (EIVMs) in closed loop. With a priori bound for the disturbing noises of an EIVM in closed loop, a frequency-domain normalized coprime factor model (NCFM) with pert...
The paper deals with the identification of dynamic discrete-time linear time-invariant errors-in-variables systems for the case of coloured output noise. The proposed algorithm is constructed within an extended bias compensated least squares framework, where the principle of the bilinear parametrisation...
With educational technology growing by leaps and bounds, synchronous online learning platforms have become a prevalent practice worldwide. Although numerous studies unraveled the behavioral intention of educational technologies with statistical methodolo
This analysis examines aggregation bias in the case of the interest rate pass-through in the Republic of Macedonia. By using bank-level data, the authors investigate whether there are heterogeneities and asymmetries in the size and speed of the adjustment of lending rates to changes in the cost...
One of the primary tools that researchers use to predict risk is the case-control study. We identify a flaw, temporal bias, that is specific to and uniquely associated with these studies that occurs when the study period is not representative of the data