radiant (version 0.1.95)

full_factor: Factor analysis (PCA)

Description

Factor analysis (PCA)

Usage

full_factor(dataset, ff_var, data_filter = "", ff_meth = "PCA", ff_number = 2, ff_rotation = "varimax")

Arguments

dataset

Dataset name (string). This can be a dataframe in the global environment or an element in an r_data list from Radiant

ff_var

Variables to include in the analysis

data_filter

Expression entered in, e.g., Data > View to filter the dataset in Radiant. The expression should be a string (e.g., "price > 10000")

ff_meth

Factor extraction method to use

ff_number

Number of factors to extract

ff_rotation

Apply varimax rotation or no rotation ("varimax" or "none")

Value

A list with all variables defined in the function as an object of class full_factor

Details

See http://vnijs.github.io/radiant/marketing/full_factor.html for an example in Radiant

See Also

summary.full_factor to summarize results

plot.full_factor to plot results

Examples

result <- full_factor("diamonds",c("price","carat","table","x","y"))
result <- full_factor("diamonds",c("price","carat","table","x","y"), ff_meth = "maxlik")
summary(result)