Improving Predictive Power of Conjoint Analysis by Constrained Parameter Estimation

1983 ◽  
Vol 20 (4) ◽  
pp. 433-438 ◽  
Author(s):  
V. Srinivasan ◽  
Arun K. Jain ◽  
Naresh K. Malhotra
Keyword(s):  
Parameter Estimation ◽  
Conjoint Analysis ◽  
Predictive Validity ◽  
Predictive Power ◽  
A Priori ◽  
A Priori Knowledge ◽  
Constrained Estimation ◽  
First Choice ◽  
Full Profile ◽  
Different Levels

The prediction of first choice preferences by the full-profile method of conjoint analysis can be improved significantly by imposing constraints on parameters based on a priori knowledge of the ordering of part worths for different levels of an attribute. Constrained estimation however, has little effect on the predictive validity of the tradeoff method because the preference judgments within rows (or columns) of tradeoff tables have largely the same role as the constraints.

Surprising Robustness of the Self-Explicated Approach to Customer Preference Structure Measurement

1997 ◽  
Vol 34 (2) ◽  
pp. 286-291 ◽  
Author(s):  
V. Srinivasan ◽  
Chan Su Park
Keyword(s):  
Utility Function ◽  
Conjoint Analysis ◽  
Predictive Validity ◽  
The Self ◽  
Preference Structure ◽  
Combined Approach ◽  
Customer Preference ◽  
Full Profile ◽  
Structure Measurement

The authors introduce customized conjoint analysis, which combines self-explicated preference structure measurement with full-profile conjoint analysis. The more important attributes for each respondent are identified first using the self-explicated approach. Full-profile conjoint analysis customized to the respondent's most important attributes then is administered. The conjoint utility function on the limited set of attributes then is combined with the self-explicated utility function on the full set of attributes. Surprisingly, the authors find that the self-explicated approach by itself yields a slightly (but not statistically significantly) higher predictive validity than does the combined approach.

Hybrid modelling of yeast production processes - combination of a priori knowledge on different levels of sophistication

1994 ◽  
Vol 17 (1) ◽  
pp. 10-20 ◽  
Author(s):  
Jörg Schubert ◽  
Rimvydas Simutis ◽  
Michael Dors ◽  
Ivo Havlík ◽  
Andreas Lübbert
Keyword(s):  
A Priori ◽  
A Priori Knowledge ◽  
Hybrid Modelling ◽  
Production Processes ◽  
Yeast Production ◽  
Different Levels ◽  
Priori Knowledge

On More Paradigms of Steganalysis

2016 ◽  
Vol 8 (2) ◽  
pp. 1-15 ◽  
Author(s):  
Xianfeng Zhao ◽  
Jie Zhu ◽  
Haibo Yu
Keyword(s):  
Real World ◽  
Systematic Approach ◽  
A Priori ◽  
Extreme Case ◽  
Design Stage ◽  
A Priori Knowledge ◽  
The Real ◽  
Different Levels ◽  
Classifier Training ◽  
Priori Knowledge

Up to now, most researches on steganalysis concentrate on one extreme case. Typically, the a priori knowledge of the embedding way and cover-media is assumed known in the classifier training and even feature design stage. However, the steganalysis in the real world is done with different levels of such knowledge so that there can be various paradigms for doing it. Although some researchers have addressed the situations, there is still a lack of a systematic approach to defining the various paradigms. In this paper, the authors give such an approach by first defining four extreme paradigms, and then defining the rest among them. Each paradigm is related with two sets of assumed known a priori knowledge respectively about the steganographic algorithm and cover-media, and each paradigm corresponds to a particular case of steganalysis. Also we will see that different paradigms can have very different aims so that the designs may be various.

Improving Predictive Power of Conjoint Analysis by Constrained Parameter Estimation

1983 ◽  
Vol 20 (4) ◽  
pp. 433 ◽  
Author(s):  
V. Srinivasan ◽  
Arun K. Jain ◽  
Naresh K. Malhotra
Keyword(s):  
Parameter Estimation ◽  
Conjoint Analysis ◽  
Predictive Power

Completely Unacceptable Levels in Conjoint Analysis: A Cautionary Note

1988 ◽  
Vol 25 (3) ◽  
pp. 293-300 ◽  
Author(s):  
Paul E. Green ◽  
Abba M. Krieger ◽  
Pradeep Bansal
Keyword(s):  
Conjoint Analysis ◽  
Predictive Validity ◽  
Cautionary Note ◽  
Theoretical Terms ◽  
Full Profile ◽  
Attribute Levels ◽  
The Impact

An experiment is reported on the extent to which respondents adhere to the implications of choosing the “completely unacceptable” level in hybrid conjoint (and related) applications. The findings indicate that the form of the instructions matters, but that respondents often ignore the implications of previous responses when responding to full-profile options containing unacceptable attribute levels. The authors discuss the impact of this inconsistency on internal predictive validity in both empirical and theoretical terms.

scholarly journals Parameter Estimation Based on Sigmoid Transform in Wideband Bistatic MIMO Radar System under Impulsive Noise Environment

Sensors ◽  
2019 ◽  
Vol 19 (2) ◽  
pp. 232 ◽  
Author(s):  
Li Li ◽  
Nicolas H. Younan ◽  
Xiaofei Shi
Keyword(s):  
Parameter Estimation ◽  
Correlation Function ◽  
Order Statistics ◽  
Impulsive Noise ◽  
A Priori ◽  
Mimo Radar ◽  
Ambiguity Function ◽  
A Priori Knowledge ◽  
Noise Environment ◽  
Priori Knowledge

Since second-order statistics-based methods rely heavily on Gaussianity assumption and fractional lower-order statistics-based methods depend on a priori knowledge of non-Gaussian noise, there remains a void in wideband bistatic multiple-input/multiple-output (MIMO) radar systems under impulsive noise. In this paper, a novel method based on Sigmoid transform was used to estimate target parameters, which do not need a priori knowledge of the noise in an impulsive noise environment. Firstly, a novel wideband ambiguity function, termed Sigmoid wideband ambiguity function (Sigmoid-WBAF), is proposed to estimate the Doppler stretch and time delay by searching the peak of the Sigmoid-WBAF. A novel Sigmoid correlation function is proposed. Furthermore, a new MUSIC algorithm based on the Sigmoid correlation function (Sigmoid-MUSIC) is proposed to estimate the direction-of-departure (DOD) and direction-of-arrival (DOA). Then, the boundness of the Sigmoid-WBAF to the symmetric alpha stable () noise, the feasibility analysis of the Sigmoid-WBAF, and complexity analysis of the Sigmoid-WBAF and Sigmoid-MUSIC are presented to evaluate the performance of the proposed method. In addition, the Cramér–Rao bound for parameter estimation was derived and computed in closed form, which shows that better performance was achieved. Simulation results and theoretical analyses are presented to verify the effectiveness of the proposed method.

On More Paradigms of Steganalysis

2020 ◽  
pp. 723-740
Author(s):  
Xianfeng Zhao ◽  
Jie Zhu ◽  
Haibo Yu
Keyword(s):  
Real World ◽  
Systematic Approach ◽  
A Priori ◽  
Extreme Case ◽  
Design Stage ◽  
A Priori Knowledge ◽  
Feature Design ◽  
Different Levels ◽  
Classifier Training ◽  
Priori Knowledge

Up to now, most researches on steganalysis concentrate on one extreme case. Typically, the a priori knowledge of the embedding way and cover-media is assumed known in the classifier training and even feature design stage. However, the steganalysis in the real world is done with different levels of such knowledge so that there can be various paradigms for doing it. Although some researchers have addressed the situations, there is still a lack of a systematic approach to defining the various paradigms. In this paper, the authors give such an approach by first defining four extreme paradigms, and then defining the rest among them. Each paradigm is related with two sets of assumed known a priori knowledge respectively about the steganographic algorithm and cover-media, and each paradigm corresponds to a particular case of steganalysis. Also we will see that different paradigms can have very different aims so that the designs may be various.

Seeing, Knowing, and Doing

2020 ◽  
Author(s):  
Robert Audi
Keyword(s):  
Practical Reasoning ◽  
Practical Knowledge ◽  
A Priori ◽  
Human Action ◽  
A Priori Knowledge ◽  
Rational Action ◽  
Reasons For Action ◽  
Discriminative Response ◽  
Rich Information ◽  
Priori Knowledge

This book provides an overall theory of perception and an account of knowledge and justification concerning the physical, the abstract, and the normative. It has the rigor appropriate for professionals but explains its main points using concrete examples. It accounts for two important aspects of perception on which philosophers have said too little: its relevance to a priori knowledge—traditionally conceived as independent of perception—and its role in human action. Overall, the book provides a full-scale account of perception, presents a theory of the a priori, and explains how perception guides action. It also clarifies the relation between action and practical reasoning; the notion of rational action; and the relation between propositional and practical knowledge. Part One develops a theory of perception as experiential, representational, and causally connected with its objects: as a discriminative response to those objects, embodying phenomenally distinctive elements; and as yielding rich information that underlies human knowledge. Part Two presents a theory of self-evidence and the a priori. The theory is perceptualist in explicating the apprehension of a priori truths by articulating its parallels to perception. The theory unifies empirical and a priori knowledge by clarifying their reliable connections with their objects—connections many have thought impossible for a priori knowledge as about the abstract. Part Three explores how perception guides action; the relation between knowing how and knowing that; the nature of reasons for action; the role of inference in determining action; and the overall conditions for rational action.

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