loadCallcenterData: Load Callcenter Data from GitHub Repository

In Rfssa: Functional Singular Spectrum Analysis

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()

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

1. 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.

2. 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.

3. Huang, J. Z., Shen, H., & Buja, A. (2008). Functional principal components analysis via penalized rank one approximation. Electronic Journal of Statistics, 2, 678-695.

4. 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.

See Also

funts

Examples

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)

Rfssa documentation built on May 29, 2024, 8:58 a.m.