loss functions
Are analysts’ loss functions asymmetric?
... quadratic loss function, and has concluded that analysts’ objective is to minimise the mean absolute forecast error (MAE), rather than mean squared ...error loss function penalises forecast optimism and ...
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Bayesian analysis of shape parameter of Lomax distribution using different loss functions
... of loss function is an integral part of Bayesian ...appropriate loss function to be used, most of the works on point estimation and point prediction assume the underlying loss function to be squared ...
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Bayesian Estimation Of Shift Point In Poisson Model Under Asymmetric Loss Functions
... asymmetric loss function and also presented a general class of precautionary loss function with quadratic loss function as a special ...These loss functions approach infinitely near the ...
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The impact of language models and loss functions on repair disfluency detection
... The remainder of this paper is structured as fol- lows. First in Section 2 we describe related work. Then in Section 3 we present some background on disfluencies and their structure. Section 4 describes appropriate ...
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US inflation expectations and heterogeneous loss functions, 1968 2010
... symmetric loss ought to be regarded as just a special case of more general loss functions, and that the presumption of symmetric loss might be misplaced for ...asymmetric loss ...
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On the Characterization of a Class of Fisher-Consistent Loss Functions and its Application to Boosting
... of loss functions that attain FC properties and provided theoretical justifications for how such loss functions can ultimately lead to optimal Bayes ...LogLog loss appears to perform ...
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Loss Functions in Restricted Parameter Spaces and Their Bayesian Applications
... a loss function for the particular application, we argue that a statistician should answer two questions: (i) is there credible information that the parameter of interest is restricted to particular space and (ii) ...
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Loss Functions for Detecting Outliers in Panel Data: An Introduction
... develops loss functions for positive ...simplest loss function that satisfies these assumptions. Loss functions are developed for more general ...of loss functions, ...
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Asymmetric Loss Functions and the Rationality of Expected Stock Returns
... asymmetric loss is not consistent with forecast ...estimated loss functions emphasize negative forecast errors more strongly than positive forecast errors, there are large and persistent deviations ...
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Training a Log Linear Parser with Loss Functions via Softmax Margin
... the loss-trained models improve over a likelihood-trained baseline, and furthermore that the exact loss functions seem to have the best ...exact loss functions despite increased ...
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Improving peak picking using multiple time-step loss functions
... of loss functions such as cross ...activation functions by identifying points of local maxima, or ...entropy loss function, which minimises the absolute difference between the output and ...
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Investigating Loss Functions and Optimization Methods for Discriminative Learning of Label Sequences
... timization functions in the literature, however, treat the whole label sequence as one label, penalizing a label sequence that has one error and a label se- quence that is all wrong in the same ...a loss ...
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Bayesian Analysis of the Mixture of Frechet Distribution under Different Loss Functions
... Inspired by above mentioned applications of mixture models, we intend to study Bayesian analysis of a 3-component mixture of the Frechet distributions with unknown mixing proportions. The parameters of component ...
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Conjugate Relation between Loss Functions and Uncertainty Sets in Classification Problems
... the loss function approach and uncertainty set approach, and to use the relation to transform learning with uncertainty sets into loss-based learning in order to clarify the statistical properties of ...
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Iterative Regularization for Learning with Convex Loss Functions
... This paper proposes and studies iterative regularization approaches for learning with convex loss functions. More precisely, we study how regularization can be achieved by early stopping an empirical ...
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Are analysts' loss functions asymmetric?
... quadratic loss function, and has concluded that analysts’ objective is to minimise the mean absolute forecast error (MAE), rather than mean squared ...error loss function penalises forecast optimism and ...
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A Note on Contribution Games with Loss Functions
... A Note on Contribution Games with Loss Functions Russo, Giuseppe and Senatore, Luigi Dipartimento di Scienze Economiche e Statistiche - University of Salerno.[r] ...
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Proportional loss functions for debris flow events
... proportional loss predictions by our ...proportional loss functions with hazard maps and databases of insurance contracts to cre- ate proper risk ...the loss predictions to offer ...
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Forecasting volatility using LINEX loss functions
... Forecasting Volatility using LINEX Loss Functions Soosung Hwang, John Knight and Stephen Satchell... A rolling sample of the past volatilities is used.[r] ...
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Adaptability and transferability of flood loss functions in residential areas
... flood loss data of past events have hardly been collected in Austria or do not contain the relevant in- formation to relate the flood losses to a certain water depth (Habersack et ...flood loss database ...
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