loadCallcenterData: Load Callcenter Data from GitHub Repository

Description

This function retrieves the Callcenter dataset from the Rfssa_dataset repository on GitHub (https://github.com/haghbinh/dataset/Rfssa_dataset). The Callcenter dataset represents a small call center for an anonymous bank. It provides precise call timing data from January 1 to December 31, 1999. The data is aggregated into 6-minute intervals on each day. The returned object is a raw dataset in dataframe format; it is not a 'funts' class object. This raw data can then be further processed and converted into a 'funts' object named 'Callcenter'. See funts for more details on working with functional time series of class 'funts'.

Usage

loadCallcenterData()

Arguments

Format

a dataframe with 87,600 rows and 5 variables:

calls: number of calls in a 6-minute aggregated interval.
u: numeric vector indicating the aggregated interval.
Date: date and time of call count recording.
Day: weekday associated with Date.
Month: month associated with Date.

References

Brown, L., Gans, N., Mandelbaum, A., Sakov, A., Shen, H., Zeltyn, S., & Zhao, L. (2005). Statistical analysis of a telephone call center: A queueing-science perspective. Journal of the American Statistical Association, 100(469), 36-50.
Shen, H., & Huang, J. Z. (2005). Analysis of call center arrival data using singular value decomposition. Applied Stochastic Models in Business and Industry, 21(3), 251-263.
Huang, J. Z., Shen, H., & Buja, A. (2008). Functional principal components analysis via penalized rank one approximation. Electronic Journal of Statistics, 2, 678-695.
Maadooliat, M., Huang, J. Z., & Hu, J. (2015). Integrating data transformation in principal components analysis. Journal of Computational and Graphical Statistics, 24(1), 84-103.

Examples

Run this code

require(fda)
# Load Callcenter data
Call_data <- loadCallcenterData()
D <- matrix(sqrt(Call_data$calls), nrow = 240)

# Define basis functions
bs1 <- create.bspline.basis(c(0, 23), 22)

Y <- funts(X = D, basisobj = bs1)