On the response time distribution in a discrete round-robin queue

1981 ◽  
Vol 16 (1) ◽  
pp. 57-62 ◽  
Author(s):  
R. Schassberger
2011 ◽  
Vol 20 (4) ◽  
pp. 1548-1557 ◽  
Author(s):  
Jun Saiki ◽  
Ayako Yoshioka ◽  
Hiroki Yamamoto

Author(s):  
Nabil Hasshim ◽  
Michelle Downes ◽  
Sarah Bate ◽  
Benjamin A. Parris

Abstract. Previous analyses of response time distributions have shown that the Stroop effect is observed in the mode (μ) and standard deviation (σ) of the normal part of the distribution, as well as its tail (τ). Specifically, interference related to semantic and response processes has been suggested to specifically affect the mode and tail, respectively. However, only one study in the literature has directly manipulated semantic interference, and none manipulating response interference. The present research aims to address this gap by manipulating both semantic and response interference in a manual response Stroop task, and examining how these components of Stroop interference affect the response time distribution. Ex-Gaussian analysis showed both semantic and response conflict to only affect τ. Analyzing the distribution by rank-ordered response times (Vincentizing) showed converging results as the magnitude of both semantic and response conflict increased with slower response times. Additionally, response conflict appeared earlier on the distribution compared to semantic conflict. These findings further highlight the difficulty in attributing specific psychological processes to different parameters (i.e., μ, σ, and τ). The effect of different response modalities on the makeup of Stroop interference is also discussed.


Psychometrika ◽  
1993 ◽  
Vol 58 (2) ◽  
pp. 281-314 ◽  
Author(s):  
Ehtibar N. Dzhafarov

2010 ◽  
Vol 14 (8) ◽  
pp. 1537-1549 ◽  
Author(s):  
M. C. Roa-García ◽  
M. Weiler

Abstract. We present a new modeling approach analyzing and predicting the Transit Time Distribution (TTD) and the Response Time Distribution (RTD) from hourly to annual time scales as two distinct hydrological processes. The model integrates Isotope Hydrograph Separation (IHS) and the Instantaneous Unit Hydrograph (IUH) approach as a tool to provide a more realistic description of transit and response time of water in catchments. Individual event simulations and parameterizations were combined with long-term baseflow simulation and parameterizations; this provides a comprehensive picture of the catchment response for a long time span for the hydraulic and isotopic processes. The proposed method was tested in three Andean headwater catchments to compare the effects of land use on hydrological response and solute transport. Results show that the characteristics of events and antecedent conditions have a significant influence on TTD and RTD, but in general the RTD of the grassland dominated catchment is concentrated in the shorter time spans and has a higher cumulative TTD, while the forest dominated catchment has a relatively higher response distribution and lower cumulative TTD. The catchment where wetlands concentrate shows a flashier response, but wetlands also appear to prolong transit time.


2010 ◽  
Vol 7 (1) ◽  
pp. 1-32 ◽  
Author(s):  
M. C. Roa-García ◽  
M. Weiler

Abstract. We present a new modeling approach analyzing and predicting the Transit Time Distribution (TTD) and the Response Time Distribution (RTD) from hourly to annual time scales as two distinct hydrological processes. The model integrates Isotope Hydrograph Separation (IHS) and the Instantaneous Unit Hydrograph (IUH) approach as a tool to provide a more realistic description of transit and response time of water in catchments. Individual event simulations and parameterizations were combined with long-term baseflow simulation and parameterizations to provide a comprehensive picture of the catchment response for a long time span for the hydraulic and isotopic processes. The proposed method was tested in three Andean headwater catchments to compare the effects of land use on hydrological response and solute transport. Results show that the characteristics of events and antecedent conditions have a significant influence on TTD and RTD, but in general the RTD of the grassland dominated catchment is concentrated in the shorter time spans and has a higher cumulative TTD, while the forest dominated catchment has a relatively longer response distribution and lower cumulative TTD. The catchment where wetlands concentrate shows a flashier response, but wetlands also appear to contribute to prolong transit time.


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