Recursive estimators of mean-areal and local bias in precipitation products that account for conditional bias

This paper is concerned with a discrete time, discrete state inventory model for items of changing quality. Items are assumed to be in one of a finite number, M, of quality classes that are ordered in such a way that Class 1 contains the best quality and the last class contains the pre-perishable quality. The changes of items' quality are dependent on the state of the ambient environment. Furthermore, at each epoch time, items of different classes may be sold or moved to a lower quality class or stay in the same class. These items are priced according to their quality, and costs are incurred as items lose quality. Based on observing the history of the inventory level and prices, we propose recursive estimators as well as predictors for the joint distribution of the accumulated losses and the state of the environment.

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Brightness local bias in children with autism spectrum disorder

Journal of Vision ◽

10.1167/12.9.793 ◽

2012 ◽

Vol 12 (9) ◽

pp. 793-793

Author(s):

S. Gori ◽

L. Ronconi ◽

F. Abalti ◽

M. Molteni ◽

T. Agostini ◽

...

Keyword(s):

Autism Spectrum Disorder ◽

Children With Autism ◽

Autism Spectrum ◽

Spectrum Disorder ◽

Local Bias

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On the Handling of Heavy Bias in a Self-Paced Task

Quarterly Journal of Experimental Psychology ◽

10.1080/14640746608400020 ◽

1966 ◽

Vol 18 (2) ◽

pp. 130-141 ◽

Cited By ~ 11

Author(s):

J. A. Leonard ◽

R. C. Newman ◽

A. Carpenter

Keyword(s):

Additive Model ◽

Input Sequence ◽

Repetition Effect ◽

Choice Task ◽

The Other ◽

Source Analysis ◽

Short Term ◽

Average Bias ◽

Local Bias

Following an earlier observation that systematic variations in performance on a task with heavy frequency imbalance was correlated with fluctuations in the amount of bias in the input programme, an experiment was carried out to establish the roles of long and short term sampling. Two groups of subjects were trained on a self-paced, five-choice task. One group's input had an average of 68 per cent. bias on one source, the other had 44 per cent. on the same source. Analysis of data was carried out on three levels of local bias for each condition, one level being identical for both conditions. It was found that responses to the biased stimuli were determined by the average bias in each input sequence and not by moment to moment variations in that bias. The effect observed originally can therefore be accounted for in terms of a relatively simple additive model which includes the “repetition effect” first described by Bertelson.

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