HIROSHI HOJO
Biographic Data
| ID | 8863388 |
|---|---|
| NAME | HIROSHI HOJO |
| GIVEN NAMES | HIROSHI |
| FAMILY NAME | HOJO |
| SIGNATURE | HOJO H |
| AFFILIATIONS | Waseda University |
| VERIFIED | No |
| TOTAL WORKS | 12 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 12 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 1982 |
| LATEST PUBLICATION YEAR | 2003 |
| H-INDEX | 0 |
A marginal maximum likelihood method for the vector threshold model to analyze dichotomous choice data
At least two types of models, the vector model and the unfolding model can be used for the analysis of dichotomous choice data taken from, for example, the pick any/ n method. The previous vector threshold models have a difficulty with estimation of the nuisance parameters such as the individual vectors and thresholds. This paper proposes a new probabilistic vector threshold model, where, unlike the former vector models, the angle that defines an…
Multidimensional unfolding analyses of ranking data for groups
One probabilistic version of Coombs' unfolding model called the MMUR (Marginalization model for the Multidimensional Unfolding analysis of Ranking data) is extended to treat ranking data for groups. One favorable feature of the model is that it can both take into consideration individual differences without estimating the subject parameters and capture the differences between the groups in a systematic manner. Another advantage lies in the fact t…
A marginalization model for the multidimensional unfolding analysis of ranking data
A marginalization model for the multidimensional unfolding analysis of ranking data is presented. A subject samples one of a number of random points that are multivariate normally distributed. The subject perceives the distances from the point to all the stimulus points fixed in the same multidimensional space. The distances are error perturbed in this perception process. He/she produces a ranking dependent on these error‐perturbed distances. The…
A new nonmetric multidimensional scaling method for sorting data
A new nonmetric multidimensional scaling method for sorting
A comparison of three response models incorporated in the latent class models for the analysis of “pick any/ n ” data
This paper presents two new response models for the analysis of preference or dominance data called “pick any/n” data. The one assumes that in Stage 1 a subject determines the number of stimuli to be chosen as most preferred, and in Stage 2 he involuntarily ranks m(=the number determined) stimuli out of all n stimuli, giving that partial ranking as a “pick any/n” response, and the other assumes that in Stage 2 the subject finds a set of m stimuli…
An analysis of three Japanese verbs of breaking
Two experiments were conducted to reveal differences in referential meaning between three Japanese verbs, waru, kudaku, and kaku, all having a semantic feature of [break] in common. In one experiment each subject drew lines of divisions on each of three squares by which he considered the square would be separated into parts when one “typically” waru-, kudaku-, and kaku-ed that square. In the other the subject was shown each of 32 different sets o…
Analysis of saliency of facial features through psychophysical scaling
Sixteen side-view smiling faces having two defining properties of the left eye and a mouth which were drawn by arcs with varying curvatures were rank ordered by 24 university students according to their perceived intensities of smiling. The analysis by a nonmetric maximum likelihood scaling method has revealed (1) that the data are approximately described by an inverse logistic function of a physical measure defined as a weighted sum of eye and m…
Psychophysical scaling of smiling faces
Sixteen schematic faces with two defining properties of eyes and lips drawn by arcs with varying curvatures were rank ordered by 37 university students according to their perceived intensities of smiling. The data were analyzed by a nonmetric maximum likelihood scaling method for directional rank order data. The analysis revealed (a) that the unconstrained model assuming no psychophysical relationships between the two curvatures of eyes and lips …
Psychophysical scaling of similarity of pentagons
Twelve pentagons, which were each variations of a standard pentagon, were rank ordered by 37 university students according to their similarity to the standard. The data were analyzed by a nonmetric maximum likelihood scaling method for rank order data. We proposed various assumptions about the manners in which physical difference measures between two stimuli were defined. The physical difference measures defined were each assumed to be linearly r…
Scaling of dot dispersion from directional rank order data
Subjective impression of dispersion of 60 or 300 dots scattered in an area of 8.2×8.2 (cm) was scaled by a nonmetric maximum likelihood scaling method for directional rank order data. The rank order data were analyzed under all combinations of three types of representation models of subjective impression of dot dispersion and five kinds of physical variables of stimuli. The analysis has revealed that the quasi-psychophysical function model (QFM) …
A maximum likelihood method for additive clustering and its applications
We present a maximum likelihood estimation procedure for Shepard-Arabie ADCLUS (for “ADditive CLUStering”) model. The major advantages of our maximum likelihood ADCLUS (MLADCLUS) over theirs are two: (1) that MLADCLUS is capable of permitting hypothesis testing;(2) that MLADCLUS distinguishes and incorporates three types of models, “the representation model, ” “the error model, ” and “the response model, ” which are necessary for any reasonable p…
Confusion-choice model for multidimensional scaling
A modification of Nakatani's model (Nakatani, 1972, Journal of Mathematical Psychology, 9, 104-127) is proposed, in which stimulus Si and response Ri are represented as a common point in a multidimensional space. When Si is presented, the distances between Si and all the responses are perturbed by an identical error process. If the distance between Si and Rj is below the response threshold tj, Rj is acceptable. The observer chooses a response fro…
No prominent works on this page.
Confusion-choice model for multidimensional scaling
A modification of Nakatani's model (Nakatani, 1972, Journal of Mathematical Psychology, 9, 104-127) is proposed, in which stimulus Si and response Ri are represented as a common point in a multidimensional space. When Si is presented, the distances between Si and all the responses are perturbed by an identical error process. If the distance between Si and Rj is below the response threshold tj, Rj is acceptable. The observer chooses a response fro…
A maximum likelihood method for additive clustering and its applications
We present a maximum likelihood estimation procedure for Shepard-Arabie ADCLUS (for “ADditive CLUStering”) model. The major advantages of our maximum likelihood ADCLUS (MLADCLUS) over theirs are two: (1) that MLADCLUS is capable of permitting hypothesis testing;(2) that MLADCLUS distinguishes and incorporates three types of models, “the representation model, ” “the error model, ” and “the response model, ” which are necessary for any reasonable p…
Scaling of dot dispersion from directional rank order data
Subjective impression of dispersion of 60 or 300 dots scattered in an area of 8.2×8.2 (cm) was scaled by a nonmetric maximum likelihood scaling method for directional rank order data. The rank order data were analyzed under all combinations of three types of representation models of subjective impression of dot dispersion and five kinds of physical variables of stimuli. The analysis has revealed that the quasi-psychophysical function model (QFM) …
Psychophysical scaling of similarity of pentagons
Twelve pentagons, which were each variations of a standard pentagon, were rank ordered by 37 university students according to their similarity to the standard. The data were analyzed by a nonmetric maximum likelihood scaling method for rank order data. We proposed various assumptions about the manners in which physical difference measures between two stimuli were defined. The physical difference measures defined were each assumed to be linearly r…
Psychophysical scaling of smiling faces
Sixteen schematic faces with two defining properties of eyes and lips drawn by arcs with varying curvatures were rank ordered by 37 university students according to their perceived intensities of smiling. The data were analyzed by a nonmetric maximum likelihood scaling method for directional rank order data. The analysis revealed (a) that the unconstrained model assuming no psychophysical relationships between the two curvatures of eyes and lips …
Analysis of saliency of facial features through psychophysical scaling
Sixteen side-view smiling faces having two defining properties of the left eye and a mouth which were drawn by arcs with varying curvatures were rank ordered by 24 university students according to their perceived intensities of smiling. The analysis by a nonmetric maximum likelihood scaling method has revealed (1) that the data are approximately described by an inverse logistic function of a physical measure defined as a weighted sum of eye and m…
An analysis of three Japanese verbs of breaking
Two experiments were conducted to reveal differences in referential meaning between three Japanese verbs, waru, kudaku, and kaku, all having a semantic feature of [break] in common. In one experiment each subject drew lines of divisions on each of three squares by which he considered the square would be separated into parts when one “typically” waru-, kudaku-, and kaku-ed that square. In the other the subject was shown each of 32 different sets o…
A comparison of three response models incorporated in the latent class models for the analysis of “pick any/ n ” data
This paper presents two new response models for the analysis of preference or dominance data called “pick any/n” data. The one assumes that in Stage 1 a subject determines the number of stimuli to be chosen as most preferred, and in Stage 2 he involuntarily ranks m(=the number determined) stimuli out of all n stimuli, giving that partial ranking as a “pick any/n” response, and the other assumes that in Stage 2 the subject finds a set of m stimuli…
A new nonmetric multidimensional scaling method for sorting data
A new nonmetric multidimensional scaling method for sorting
A marginalization model for the multidimensional unfolding analysis of ranking data
A marginalization model for the multidimensional unfolding analysis of ranking data is presented. A subject samples one of a number of random points that are multivariate normally distributed. The subject perceives the distances from the point to all the stimulus points fixed in the same multidimensional space. The distances are error perturbed in this perception process. He/she produces a ranking dependent on these error‐perturbed distances. The…
Multidimensional unfolding analyses of ranking data for groups
One probabilistic version of Coombs' unfolding model called the MMUR (Marginalization model for the Multidimensional Unfolding analysis of Ranking data) is extended to treat ranking data for groups. One favorable feature of the model is that it can both take into consideration individual differences without estimating the subject parameters and capture the differences between the groups in a systematic manner. Another advantage lies in the fact t…
A marginal maximum likelihood method for the vector threshold model to analyze dichotomous choice data
At least two types of models, the vector model and the unfolding model can be used for the analysis of dichotomous choice data taken from, for example, the pick any/ n method. The previous vector threshold models have a difficulty with estimation of the nuisance parameters such as the individual vectors and thresholds. This paper proposes a new probabilistic vector threshold model, where, unlike the former vector models, the angle that defines an…
Mathematics (12 works) · Computer Science (10 works) · Statistics (9 works) · Artificial Intelligence (7 works) · Artificial Intelligence (7 works) · Scaling (7 works) · Psychology (6 works) · Geometry (5 works) · Multidimensional scaling (5 works) · Sensory Analysis and Statistical Methods (5 works)