Multidimensional Scaling, Nummer 11SAGE, 1978 - 93 pagina's Outlines a set of techniques that enable a researcher to discuss the 'hidden structure' of large databases. These techniques use proximities, measures which indicate how similar or different objects are, to find a configuration of points which reflects the structure in the data. |
Inhoudsopgave
Editors Introduction | 5 |
Interpretation of the Configuration | 30 |
Dimensionality | 48 |
ThreeWay Multidimensional Scaling | 60 |
Preparing the Input for Multidimensional Scaling | 73 |
Notes | 82 |
Other Uses for Lines and the Horseshoe Phenomenon | 88 |
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Veelvoorkomende woorden en zinsdelen
analyzed approach Bell Laboratories Bikol BRAZIL clusters computational procedure computer program CONGO corresponds CUBA curve data values described desirable determined dimension weights dimensional interpretation directions discussed dissimilarities EGYPT elbow error level Euclidean distances example f-stress factor analysis Figure 5A formula four-dimensional geometric global minimum higher-dimensional imities important indicate INDSCAL analysis INDSCAL model ISRAEL Kruskal KYST and M-D-SCAL linear regression lines local minimum matrix of profile MDS configuration mean measure method metric scaling Monte Carlo Morse code MULTIDIMENSIONAL SCALING multiple correlation multiple regression nations neighborhoods nonmetric scaling objective function obtained pair plot points possible PROFILE DISTANCE profile proximities prox proximities data proximity matrix R₁ rating scales reasonable relationship root mean square Roskam RUSSIA scatter diagram Shepard shown in Figure signals similarity sion square starting configuration statistical stimuli stress values subjects techniques three-way tion traits two-dimensional configuration two-way MDS value of stress variable versus YUGOSLAVIA
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