Title: Index Construction for Time Series Data
Imports: KernSmooth, fGarch, lubridate, xts, RcppBDT, zoo
Description: Derivation of indexes for benchmarking purposes. The methodology of the CRyptocurrency IndeX (CRIX) family with flexible number of constituents is implemented. Also functions for market capitalization and volume weighted indexes with fixed number of constituents are available. The methodology behind the functions provided gets introduced in Trimborn and Haerdle (2018) <doi:10.1016/j.jempfin.2018.08.004>.

Description: Derivation of indexes for benchmarking purposes. A methodology with flexible number of constituents is implemented. Also functions for market capitalization and volume weighted indexes with fixed number of constituents are available. The main function of the package, indexComp(), provides the derived index, suitable for analysis purposes. The functions indexUpdate(), indexMemberSelection() and indexMembersUpdate() are components of indexComp() and enable one to construct and continuously update an index, e.g. for display on a website. The methodology behind the functions provided gets introduced in Trimborn and Haerdle (2018) <doi:10.1016/j.jempfin.2018.08.004>.

Description: Computes bilateral and multilateral index numbers.
It has support for several standard bilateral indices as well as
the GEKS multilateral index number methods
(see Ivancic, Diewert and Fox (2011) <doi:10.1016/j.jeconom.2010.09.003>) .
It also supports updating of GEKS indexes using several splicing methods.

It has support for many standard bilateral indexes as well as
multilateral index number methods such as GEKS, GEKS-Tornqvist
(or CCDI), Geary-Khamis and the weighted time product dummy
(for details on these methods see Diewert and Fox (2020)
It also supports updating of multilateral indexes using

Suggests: testthat, knitr, rmarkdown, covr, tidyr

Description: We provide an R tool to determine index numbers. It is a measure of the evolution of a fixed magnitude for only a product of for several products. It is very useful in Social Sciences. Among others, we obtain simple index numbers (in chain or in serie), index numbers for not only a product or weighted index numbers as the Laspeyres index (Laspeyres, 1864), the Paasche index (Paasche, 1874) or the Fisher index (Lapedes, 1978).