lba
(Package: lba) :
Latent Budget Analysis (LBA) for Compositional Data
Latent budget analysis (LBA) is a method for the analysis of contingency tables, from where the compositional data is derived. It is used to understand the relationship between the table rows and columns, where the rows denote the categories of the explanatory variable and the columns denote the categories of the response variable.
goodnessfit
(Package: lba) :
Goodness of Fit results for Latent Budget Analysis
The goodness of fit results assesses how well the model fits the data. It consists of measures of the resemblance between the observed and the expected data, and the parsimony of the model.
S3 methods for lba objects. It's possible two types of visualisation: the lba type, suggested by van der Ark (1999) and correspondence analysis suggested by Jelihovschi (2011).
votB
(Package: lba) :
Voting Behaviour in Netherlands
The votB data frame has 8971 rows and 2 columns. The raw data refers to the type of the city and the political party which each participant voted for in the 1986 general elections in the Netherlands.
Latent budget analysis (LBA) is a method for the analysis of contingency tables, from where the compositional data is derived. It is used to understand the relationship between the table rows and columns, where the rows denote the categories of the explanatory variable and the columns denote the categories of the response variable.