bribery

The data set refers to a collection of 55 articles on Bribery cases from central Russian newspapers 1999-2000 (Mirkin, 2005). The variables reflect the following fivefold structure of bribery situations: two interacting sides - the office and the client, their interaction, the corrupt service rendered, and the environment in which it all occurs. These structural aspects can be characterized by eleven variables that have been manually recovered from the newspaper articles.

datasets

A class of methods that combine dimension reduction and clustering of continuous, categorical or mixed-type 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 2017; <DOI:10.1007/s11336-016-9514-0>), which combine multiple correspondence analysis with K-means. For mixed-type data, it provides mixed Reduced K-means and mixed Factorial K-means (van de Velden, Iodice D'Enza and Markos 2019; <DOI:10.1002/wics.1456>), which combine PCA for mixed-type data with K-means.

Angelos Markos

clustrd

Methods for Joint Dimension Reduction and Clustering

bribery function

A data frame with 55 observations on 11 categorical variables.<dl class="dl-horizontal">
 <dt><code>Of</code></dt><dd>Type of Office</dd>
 <dt><code>Cl</code></dt><dd>Level of Client</dd>
 <dt><code>Serv</code></dt><dd>Type of service: obstruction of justice, favours, cover-up, change of category, extortion of money for rendering free services</dd>
 <dt><code>Occ</code></dt><dd>Frequency of occurrence</dd>
 <dt><code>Init</code></dt><dd>Who initiated the bribery act</dd>
 <dt><code>Brib</code></dt><dd>Bribe Level in $</dd>
 <dt><code>Typ</code></dt><dd>Type of corruption</dd>
 <dt><code>Net</code></dt><dd>Corruption network</dd>
 <dt><code>Con</code></dt><dd>Condition of corruption</dd>
 <dt><code>Bran</code></dt><dd>Branch at which the corrupt service occurred</dd>
 <dt><code>Pun</code></dt><dd>Punishment</dd>
 </dl>

Format

Bribery cases in Russia — bribery

A data frame with 55 observations on 11 categorical variables.<dl class='dl-horizontal'>
 <dt><code>Of</code></dt><dd>Type of Office</dd>
 <dt><code>Cl</code></dt><dd>Level of Client</dd>
 <dt><code>Serv</code></dt><dd>Type of service: obstruction of justice, favours, cover-up, change of category, extortion of money for rendering free services</dd>
 <dt><code>Occ</code></dt><dd>Frequency of occurrence</dd>
 <dt><code>Init</code></dt><dd>Who initiated the bribery act</dd>
 <dt><code>Brib</code></dt><dd>Bribe Level in $</dd>
 <dt><code>Typ</code></dt><dd>Type of corruption</dd>
 <dt><code>Net</code></dt><dd>Corruption network</dd>
 <dt><code>Con</code></dt><dd>Condition of corruption</dd>
 <dt><code>Bran</code></dt><dd>Branch at which the corrupt service occurred</dd>
 <dt><code>Pun</code></dt><dd>Punishment</dd>
 </dl>

bribery: Bribery cases in Russia

Description

Usage

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Format

References

Examples