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earowang
hts:Hierarchical and Grouped Time Series
Provides methods for analysing and forecasting hierarchical and grouped time series. The available forecast methods include bottom-up, top-down, optimal combination reconciliation (Hyndman et al. 2011) <doi:10.1016/j.csda.2011.03.006>, and trace minimization reconciliation (Wickramasuriya et al. 2018) <doi:10.1080/01621459.2018.1448825>.
Maintained by Earo Wang. Last updated 3 months ago.
110 stars 9.69 score 215 scripts 5 dependents
smac-group
simts:Time Series Analysis Tools
A system contains easy-to-use tools as a support for time series analysis courses. In particular, it incorporates a technique called Generalized Method of Wavelet Moments (GMWM) as well as its robust implementation for fast and robust parameter estimation of time series models which is described, for example, in Guerrier et al. (2013) <doi: 10.1080/01621459.2013.799920>. More details can also be found in the paper linked to via the URL below.
Maintained by Stéphane Guerrier. Last updated 2 years ago.
rcpprcpparmadillosimulationtime-seriestimeseriestimeseries-dataopenblascpp
15 stars 7.68 score 59 scripts 4 dependents
doer0
ibd:Incomplete Block Designs
A collection of several utility functions related to binary incomplete block designs. Contains function to generate A- and D-efficient binary incomplete block designs with given numbers of treatments, number of blocks and block size. Contains function to generate an incomplete block design with specified concurrence matrix. There are functions to generate balanced treatment incomplete block designs and incomplete block designs for test versus control treatments comparisons with specified concurrence matrix. Allows performing analysis of variance of data and computing estimated marginal means of factors from experiments using a connected incomplete block design. Tests of hypothesis of treatment contrasts in incomplete block design set up is supported.
Maintained by B N Mandal. Last updated 1 years ago.
2.95 score 33 scripts 3 dependents