Change detection for uncertain autoregressive dynamic models through nonparametric estimation

Statistical Methodology ◽

10.1016/j.stamet.2016.08.003 ◽

2016 ◽

Vol 33 ◽

pp. 96-113 ◽

Cited By ~ 3

Author(s):

Nadine Hilgert ◽

Ghislain Verdier ◽

Jean-Pierre Vila

Keyword(s):

Change Detection ◽

Nonparametric Estimation ◽

Dynamic Models

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Nonparametric estimation and testing linear hypotheses in the linear regression model

Optimization ◽

10.1080/02331937508842249 ◽

1975 ◽

Vol 6 (2) ◽

pp. 269-283

Author(s):

Jana Jureková

Keyword(s):

Linear Regression ◽

Regression Model ◽

Nonparametric Estimation ◽

Linear Regression Model ◽

Testing Linear

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Vivid Imagers Are Better at Detecting Salient Changes

Journal of Individual Differences ◽

10.1027/1614-0001.27.4.218 ◽

2006 ◽

Vol 27 (4) ◽

pp. 218-228 ◽

Cited By ~ 13

Author(s):

Paul Rodway ◽

Karen Gillies ◽

Astrid Schepman

Keyword(s):

Individual Differences ◽

Change Detection ◽

Visual Imagery ◽

Detection Task ◽

Level Of Detail ◽

Detection Accuracy ◽

Change Detection Task ◽

Term Change ◽

High Level

This study examined whether individual differences in the vividness of visual imagery influenced performance on a novel long-term change detection task. Participants were presented with a sequence of pictures, with each picture and its title displayed for 17 s, and then presented with changed or unchanged versions of those pictures and asked to detect whether the picture had been changed. Cuing the retrieval of the picture's image, by presenting the picture's title before the arrival of the changed picture, facilitated change detection accuracy. This suggests that the retrieval of the picture's representation immunizes it against overwriting by the arrival of the changed picture. The high and low vividness participants did not differ in overall levels of change detection accuracy. However, in replication of Gur and Hilgard (1975) , high vividness participants were significantly more accurate at detecting salient changes to pictures compared to low vividness participants. The results suggest that vivid images are not characterised by a high level of detail and that vivid imagery enhances memory for the salient aspects of a scene but not all of the details of a scene. Possible causes of this difference, and how they may lead to an understanding of individual differences in change detection, are considered.

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