Antevs

Antevs

Time-series arise in situations where a value is measured through time, generally at discrete intervals. Annual intervals commonly occur in natural systems due to seasonal variations in temperature, as displayed in proglacial varves, tree-rings, and glacial ice. Antevs (Automated Numerical Time-series Evaluation of Varying Sequences) is designed primarily to work with such natural time-series, but can be applied to other discrete time-series as well. Antevs is designed to aid in correlation of time-series, where an undated times-series, the unknown, is compared to a previously dated series, the chronology, to determine if they overlap in time and to date the unknown series.

Antevs was developed for the correlation of proglacial varve sequences (Rayburn and Vollmer, 2013), however it includes standard techniques for matching tree-ring sequences, and can convert files between varve and tree-ring formats. It includes routines for reading the Velmex UniSlide digital readout used for tree-ring measurements. A common problem with natural time-series is that of missing data, often due to broken cores. Antevs includes interactive procedures to correlate sequences, such as broken cores, that contain missing values.

Antevs is designed to be user friendly and easy to use, with powerful analytical tools under the hood. It is designed for ease of use, and undergoes extensive testing by undergraduates working on research projects in John Rayburn's varve and tree-ring laboratory at SUNY New Paltz

Antevs is developed on Macintosh OS X and is compiled natively for Macintosh OS X, Windows, and Linux. It is not cross-compiled or interpreted, and does not require any additional libraries or interpreters. Currently testing is done on OS X 10.6, 10.10, Windows XP, Windows 7, and Linux Ubuntu. User input is appreciated to improve operation on various platforms.

Antevs is written by Frederick W. Vollmer. It is free software, but may not be redistributed or posted online without the author's permission. Any significant usage, such as a resulting presentation or publication, must include attribution to the program and author. This program is distributed in the hope that it will be useful, but without any warranty; without even the implied warranty of merchantability or fitness for a particular purpose. Please read the accompanying User Manual file for license and additional information.

Example Correlation

Correlogram A) Hudson and Connecticut River Valley raw (top) and detrended (bottom) North American Varve Chronology data (NAVC, see link on sidebar). The raw data is detrended using a 16 term Fourier filter to remove long wavelength variations, and standardized to account for thickness variations between proxmal and distal varves.

B) Correlogram produced by cross-correlation of the detrended data in A. The correlogram shows a spike corresponding to a match at 0 years offset, with a correlation of r = 0.64, and significance t = 9.57.

Modified from Rayburn and Vollmer, 2013.