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

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 information research was once broadly defined within the prior chapters of this publication. It used to be followed via a sequence of benchmark actions related to a few respectable 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 records (ONS) from the uk, the Inspection Generale de los angeles Securite Sociale (IGSS) from Luxembourg 1 and marginally the collage of Athens . The primary objective of those benchmark actions was once to illustrate the usefulness of symbolic information research for functional statistical exploitation and research of reputable statistical facts. This bankruptcy goals to file in short on those actions via providing a few signifi­ cant insights into functional effects bought via the benchmark companions in utilizing the SODAS software program package deal as defined in bankruptcy 14 below.

Show description

Read or Download Analysis of Symbolic Data: Exploratory Methods for Extracting Statistical Information from Complex Data PDF

Similar analysis books

CIM Revision cards: Analysis and Evaluation

Designed particularly with revision in brain, the CIM Revision playing cards supply concise, but basic info to aid scholars in passing the CIM tests as simply as attainable. a transparent, conscientiously established format aids the training approach and guarantees the most important issues are lined in a succinct and available demeanour.

Analysis of Variance and Functional Measurement: A Practical Guide includes

This booklet is a transparent and easy consultant to research of variance, the spine of experimental examine. it's going to assist you interpret statistical effects and translate them into prose that may truly inform your viewers what your information is asserting. that can assist you get to grips with the ideas utilized in research of variance, there are many end-of-chapter perform issues of instructed solutions.

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

Sample text

The input of DB2S0 (see Chapter 5) is a query to a data base. Its output is a symbolic data table. Having obtained this data table, any of the previous SDA methods can be applied. 2 An Illustrative Example The general aim and strategy of SODAS can be illustrated by the following example: We consider a set of households which are each characterized by its region REGION, the number of bedrooms BED, the number of dining-living rooms DILTV, and its socio-economic group SPC . 5: ID REGION BED DILIV SPC 11404 North - lid etropolitan '2 bedrooms' 'one dining-living' 'Farmers' ----,,11405 North - Metropolitan '2 bedrooms' 'one dining-living' 'Service' 11406 North - Metropolitan 'one bedroom' '3 dining-living' 'Service' ..

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' ...

Without nested brackets) are used. -H. Bock et al. ), Analysis of Symbolic Data © Springer-Verlag Berlin Heidelberg 2000 40 3 Symbolic Data In fact, data entries of the interval or distribution type are typical for applications • of the SODAS software. 2: Symbolic data for classes of individuals: Two-level paradigm Symbolic data types are particularly well suited to situations where we have to analyze not single individuals (or 'first order objects'), but more or less homogeneous classes of indiv'iduals ('aggregate objects', 'super-individuals', 'second order objects').

Download PDF sample

Rated 4.51 of 5 – based on 18 votes

Related posts