PVplr: R Package Implementation of Multiple Filters and Algorithms for Time-series Performance Loss Rate Analysis

2020 ◽  
Author(s):  
Alan J. Curran ◽  
Tyler L. Burleyson ◽  
Kunal Rath ◽  
Arthur S. Xin ◽  
Sascha Lindig ◽  
...  
Keyword(s):  
Time Series ◽  
Loss Rate ◽  
R Package ◽  
Performance Loss ◽  
Rate Analysis

scholarly journals The runaway supergiant HD 188209 (O9.5Iab): a binary or a pulsating star?

1999 ◽  
Vol 193 ◽  
pp. 69-70
Author(s):  
Garik Israelian ◽  
Artemio Herrero ◽  
E. Santolaya-Rey ◽  
A. Kaufer ◽  
F. Musaev ◽  
...  
Keyword(s):  
Time Series ◽  
High Resolution ◽  
Mass Loss ◽  
Radial Velocity ◽  
Loss Rate ◽  
State Of The Art ◽  
Mass Loss Rate ◽  
Fundamental Parameters ◽  
Binary Nature ◽  
Period 2

We report radial velocity studies of photospheric absorption lines from spectral time series of the late O-type runaway supergiant HD 188209. Radial velocity variations with a quasi-period ∼ 2 days have been detected in high-resolution echelle spectra and most probably indicate that the supergiant is pulsating. Night-to-night variations in the position and strength of the central emission reversal of the Hα profile have been observed. The fundamental parameters of the star have been derived using state-of-the-art plane-parallel and unified non-LTE model atmospheres, these last including the mass-loss rate. The binary nature of this star is not suggested either from Hipparcos photometry or from radial-velocity curves.

scholarly journals KarsTS: an R package for microclimate time series analysis

2019 ◽  
Vol 12 (4) ◽  
pp. 685-697
Author(s):  
M. Sáez ◽  
C. Pla ◽  
S. Cuezva ◽  
D. Benavente
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
R Package ◽  
Series Analysis

scholarly journals TSIS: an R package to infer alternative splicing isoform switches for time-series data

2017 ◽  
Vol 33 (20) ◽  
pp. 3308-3310 ◽  
Author(s):  
Wenbin Guo ◽  
Cristiane P G Calixto ◽  
John W S Brown ◽  
Runxuan Zhang
Keyword(s):  
Time Series ◽  
Alternative Splicing ◽  
Time Series Data ◽  
R Package ◽  
Series Data

scholarly journals Identification and visualisation of differential isoform expression in RNA-seq time series

2017 ◽  
Author(s):  
María José Nueda ◽  
Jordi Martorell-Marugan ◽  
Cristina Martí ◽  
Sonia Tarazona ◽  
Ana Conesa
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Expression Patterns ◽  
R Package ◽  
Series Data ◽  
Rna Seq ◽  
Sequencing Technologies ◽  
Isoform Expression ◽  
Time Series Data Analysis ◽  
Differential Isoform Expression

AbstractAs sequencing technologies improve their capacity to detect distinct transcripts of the same gene and to address complex experimental designs such as longitudinal studies, there is a need to develop statistical methods for the analysis of isoform expression changes in time series data. Iso-maSigPro is a new functionality of the R package maSigPro for transcriptomics time series data analysis. Iso-maSigPro identifies genes with a differential isoform usage across time. The package also includes new clustering and visualization functions that allow grouping of genes with similar expression patterns at the isoform level, as well as those genes with a shift in major expressed isoform. The package is freely available under the LGPL license from the Bioconductor web site (http://bioconductor.org).

scholarly journals SADI: Sequence Analysis Tools for Stata

2017 ◽  
Vol 17 (3) ◽  
pp. 546-572 ◽  
Author(s):  
Brendan Halpin
Keyword(s):  
Time Series ◽  
Sequence Analysis ◽  
Life Course ◽  
Sequence Data ◽  
R Package ◽  
Optimal Matching ◽  
Matching Algorithm ◽  
Analysis Tools ◽  
Categorical Time Series ◽  
Main Components

The SADI package provides tools for sequence analysis, which focuses on the similarity and dissimilarity between categorical time series such as life-course trajectories. SADI‘s main components are tools to calculate intersequence distances using several different algorithms, including the optimal matching algorithm, but it also includes utilities to graph, summarize, and manage sequence data. It provides similar functionality to the R package TraMineR and the Stata package SQ but is substantially faster than the latter.

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