April 20, 2017

Download Analysis of Symbolic Data: Exploratory Methods for by Edwin Diday (auth.), Prof. Dr. Hans-Hermann Bock, Prof. PDF

By Edwin Diday (auth.), Prof. Dr. Hans-Hermann Bock, Prof. Edwin Diday (eds.)

Raymond Bisdorff CRP-GL, Luxembourg the improvement of the SODAS software program in response to symbolic info research was once commonly defined within the earlier chapters of this booklet. It used to be followed through a sequence of benchmark actions concerning a few legitimate statistical institutes all through Europe. companions in those benchmark actions have been the nationwide Statistical Institute (INE) of Portugal, the Instituto Vasco de Estadistica Euskal (EUSTAT) from Spain, the workplace For nationwide information (ONS) from the uk, the Inspection Generale de l. a. Securite Sociale (IGSS) from Luxembourg 1 and marginally the college of Athens . The relevant target of those benchmark actions was once to illustrate the usefulness of symbolic facts research for sensible statistical exploitation and research of reliable statistical information. This bankruptcy goals to file in brief on those actions by way of featuring a few signifi­ cant insights into useful effects got by way of the benchmark companions in utilizing the SODAS software program package deal as defined in bankruptcy 14 below.

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Additional resources for Analysis of Symbolic Data: Exploratory Methods for Extracting Statistical Information from Complex Data

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Two nodes x, y of 1{, must necessarily take into account the hierarchical structure of 1{. , by the path distance in the tree describing 1{. 5 31 Data Vectors and Data Matrix Data Vectors and the Data Matrix In practice, when investigating a set D = {I, ... , n} of individuals we typically do not record only one single variable, but several variables simultaneously, Y 1 , ... , Yp say. 4) j=l which takes its values in the Cartesian product X of the corresponding variablespecific domains Yl, ...

In particular, in order to keep this information comprehensible, there was the need to aggregate the recorded individual data by considering classes or groups of individuals ('super-objects', second-order objects) instead of single individuals (first-order objects) only and to describe the properties of these classes by new variables and data types which are here termed 'symbolic variables' and will be described in Chapter 3. 3) . ) which are collected in a set D = {l, . -H. Bock et al. 3 Quantitative Variables 25 --------------------------~ (population, universe, .

East - anglia 12112 12112 East - anglia 12112 Greater - LondonN E .. ... .. 5: Standard data table for households - In census data, where there is a huge set of households, we can summarize them by describing each region by the households of their inhabitants. 6. 16 1 Symbolic Data Analysis and the SODAS Project REGION BED DILIV SPC NoTth - Metropolitan '2 bedrooms' 'one dining-living' 'Farmers' North - Metropolitan '2 bedrooms' 'one dining-living' 'Service' North - Metropolitan 'one bedroom' '3 dining-living' 'Service' ...

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