underwear


The dataset comes from a large survey conducted by a South Korean underwear manufacturer in 1997. 664 South Korean consumers were asked to provide responses for three multiple-choice items: attributes when considering a brand of underwear to purchase (15 attributes), preferred brand of underwear (8 brands) and consumer age (3 levels).


datasets

A class of methods that combine dimension reduction and clustering of continuous or categorical data. For continuous data, the package contains implementations of factorial K-means (Vichi and Kiers 2001; <DOI:10.1016/S0167-9473(00)00064-5>) and reduced K-means (De Soete and Carroll 1994; <DOI:10.1007/978-3-642-51175-2_24>); both methods that combine principal component analysis with K-means clustering. For categorical data, the package provides MCA K-means (Hwang, Dillon and Takane 2006; <DOI:10.1007/s11336-004-1173-x>), i-FCB (Iodice D'Enza and Palumbo 2013, <DOI:10.1007/s00180-012-0329-x>) and Cluster Correspondence Analysis (van de Velden, Iodice D'Enza and Palumbo 2016; <DOI:10.1007/s11336-016-9514-0>), which combine multiple correspondence analysis with K-means.

Angelos Markos

clustrd

Methods for Joint Dimension Reduction and Clustering

underwear function

A data frame with 664 observations on the following variables.
  <dl> </dl> 

Format

Hwang, H., Dillon, W. R. & Takane, Y. (2006). An extension of multiple correspondence analysis for identifying heterogenous subgroups of respondents. <em>Psychometrika</em>, 71, 161-171.

underwear: South Korean Underwear

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