Semi-parameter Stochastic Frontier Model and Its Algorithm Based on Multivariate Matrix for Psycho-measurement
Los Angeles, CA
March 31, 2009 to April 2, 2009
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CSIE.2009.247
As the results of the psycho-scales are single and simple, we attempt to apply the semi-parameter stochastic frontier model in econometrics, which developed from the stochastic frontier linear model and combined linear regression and non-parameter regression, to psycho-measurement. By means of this innovation, we can overcome the shortcomings of traditional psycho-scale we stated above and make the individual who receives the psycho-measurement much clear about his proportional level of the people who also get the same psycho-scale tests. Via this model, we find the multidimensional data exist, and the multidimensional data are the basis of the higher research, so the storage, operation, structure about the multidimensional data are required, to achieve an efficient decision-making.
Haiying Wu, Hengqing Tong, Yingbi Zhang, "Semi-parameter Stochastic Frontier Model and Its Algorithm Based on Multivariate Matrix for Psycho-measurement", CSIE, 2009, 2009 WRI World Congress on Computer Science and Information Engineering, CSIE, 2009 WRI World Congress on Computer Science and Information Engineering, CSIE 2009, pp. 396-399, doi:10.1109/CSIE.2009.247