Packaged: 2019-05-24 11:22:49 UTC; LeodolterM

Packaged: 2019-06-27 07:58:43 UTC; LeodolterM

parallelDist, microbenchmark, rucrdtw, proxy, R.rsp,

Packaged: 2019-12-18 11:50:01 UTC; LeodolterM

Packaged: 2020-10-09 08:00:48 UTC; Leodolter

Description: The Dynamic Time Warping (DTW) distance measure for time series allows non-linear alignments of time series to match  similar patterns in time series of different lengths and or different speeds. IncDTW is characterized by (1) the incremental calculation of DTW (reduces runtime complexity to a linear level for updating the DTW distance) - especially for life data streams or subsequence matching, (2) the vector based implementation of DTW which is faster because no matrices are allocated (reduces the space complexity from a quadratic to a linear level in the number of observations) - for all runtime intensive DTW computations, (3) the subsequence matching algorithm runDTW, that efficiently finds the k-NN to a query pattern in a long time series, and (4) C++ in the heart. For details about DTW see the original paper "Dynamic programming algorithm optimization for spoken word recognition" by Sakoe and Chiba (1978) <DOI:10.1109/TASSP.1978.1163055>. For details about this package, Dynamic Time Warping and Incremental Dynamic Time Warping please see "IncDTW: An R Package for Incremental Calculation of Dynamic Time Warping" by Leodolter et al. (2021) <doi:10.18637/jss.v099.i09>.
Packaged: 2021-09-22 18:38:42 UTC; Leodolter

Packaged: 2022-03-12 10:44:06 UTC; leodolter

Title: Comparison of Means for the Incomplete Paired Data
person("Desale", "Habtzghi", email = "dhabtzgh@depaul.edu", role = c("aut", "cre")),
person("Yilin", "Zhang", email = "yz112529@gmail.com", role="aut"),
Description: Implements a variety of nonparametric and parametric methods that are commonly used when the data set is a mixture of paired observations and independent samples. The package also calculates and returns values of different tests with their corresponding p-values.
Bhoj, D. S. (1991) <doi:10.1002/bimj.4710330108> "Testing equality of means in the presence of correlation and missing data".
Dubnicka, S. R., Blair, R. C., and Hettmansperger, T. P. (2002) <doi:10.22237/jmasm/1020254460> "Rank-based procedures for mixed paired and two-sample designs".
Einsporn, R. L. and Habtzghi, D. (2013) <https://pdfs.semanticscholar.org/89a3/90bafeb2bc41ed4414533cfd5ab84a6b54b6.pdf> "Combining paired and two-sample data using a permutation test".
Ekbohm, G. (1976) <doi:10.1093/biomet/63.2.299> "On comparing means in the paired case with incomplete data on both responses".
Lin, P. E. and Stivers, L. E. (1974) <doi:10.1093/biomet/61.2.325> On difference of means with incomplete data".
Maritz, J. S. (1995) <doi:10.1111/j.1467-842x.1995.tb00649.x> "A permutation paired test allowing for missing values".