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Table 1 shows the results of the study. For each model, the optimal parameters and a measure of the model apos;s average error are presented. Average error provides a single measure of performance that can be used to compare models, it is defined below.

in Investigating The Performance Of Several Aac User Models
by Bryan J. Moulton, Gregory W. Lesher, D. Jeffery Higginbotham, Ph. D, Ph. D
"... In PAGE 3: ... error: 32.62% Table1 : User model parameter estimation results DISCUSSION The average errors of models 2-4 is significantly less than that for model 1, with the most sophisticated (model 4) yielding an improvement of 9.85 and 15.... ..."

Table 4: Half-Life of Top k Search Results Type Top

in Agreeing to disagree: Search engines and their public interfaces
by Frank Mccown 2007
"... In PAGE 7: ...5. The observed and predicted half-lives for each search en- gine is presented in Table4 . For top 100 results, the pre- dicted half-lives for both interfaces lie close to each other.... ..."
Cited by 2

Table 4. Experiment 2, Comparison

in Statistical Decision Theory and the Selection of Rapid, Goal-Directed Movements
by Julia Trommershäuser, Laurence T. Maloney, Michael S. Landy
"... In PAGE 11: ... The slope estimates were compared with a slope of 1, indicating perfect correspondence between the data and model. Table4 contains the slope estimates and the corresponding p values (df ; 192, varying ac- cording to the exact number of data recorded per subject, data that Bonferroni corrected for number of subjects; sig- nificant deviations from the model predictions with p , 0.05 marked by an asterisk; please contact authors for details).... ..."

TABLE 6 Model Predictions

in Technology Adoption, Learning by Doing, and Productivity: A Study of Steel Refining Furnaces,” Working Paper
by Hiroshi Ohashi, Tsuyoshi Nakamura 2005
Cited by 1

Table 5. Results of analyses comparing alternative multiple regression models prediction of controller activity.

in Controller Taskload 6. Performing Organization Code
by Carol A. Manning, Elaine M. Pfleiderer, Manning Ca, Pfleiderer Em 2006
"... In PAGE 9: ... We used a method that allowed us to compare specific regression models instead of an analysis such as stepwise linear regression because we wanted to assess the relative contribution of specific variables to the model rather than simply those variables that made statistically significant contributions, such as would result when conducting a multiple regression analysis. Table5 shows the results of these analyses. Row 1 shows the multiple correlation of the full model containing all three predictor variables (Number of Aircraft, Complexity Rating, and Complexity Value) with the criterion variable (number of R and RA controller data entries).... ..."

TABLE 5 SUMMARY OF MODEL PREDICTIONS

in THE ASTROPHYSICAL JOURNAL, 565 280296, 2002 January 20
by The American Astronomical, Igor V. Moskalenko, Andrew W. Strong, Jonathan F. Ormes, Marius S. Potgieter

TABLE 6. Results for flux distribution reliability test: predicted and measured fragment mass H20851M-57H20852H11001 distributions of key amino acids when 1-13C-labeled lactate medium was used for shake flask culture (n H11005 2)a

in unknown title
by unknown authors 2006

Table 6 Background data for model prediction

in Optimal Design of Internet-based Auctions
by Carrie Beam, Arie Segev, J. George Shanthikumar 1999
"... In PAGE 3: ........... 24 Table6 Background data for model prediction .... ..."
Cited by 2

Table 7: A comparison of the tted parameter values for each patient apos;s original naming performance and the performance obtained after a recovery period. Original Recovery

in An Evaluation of a Computational Model of Lexical Access: Comments on Dell et al. (1997)
by Wheeler Ruml, Alfonso Caramazza 1997
"... In PAGE 32: ... To test the model apos;s predictions, we need to compare the tted parameter values (from Table 6) with those found for the original data (from Table 3). This comparison is distilled in Table7 . The new parameters lie in the rectangle between the original t and the normal values of 0.... ..."
Cited by 3

Table 4. Fault class model prediction result

in Assessing SRAM Test Coverage for Sub--Micron CMOS Technologies
by Vonkyoung Kim, Tom Chen 1997
"... In PAGE 4: ... As a consequence, we can predict the probability for each fault class if the process technology is known. Table4 shows model prediction result compared with extracted data. The model prediction results showed well below 10% errors except SOF for process A.... ..."
Cited by 3
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