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Welcome to the avar package

This package provides the tools necessary to compute the empirical Allan Variance (AV) and use it to estimate the parameters of (latent) time series models. The estimation of the Allan Variance is performed through the estimator proposed by Allan (1966) and, based on this quantity, the Allan Variance Linear Regression (AVLR) approach (or Allan Variance Slope Method) is often used by engineers to retrieve the parameters of time series models which are assumed to underlie the observed signals (see for example Guerrier, Molinari, and Stebler 2016). These estimators are implemented in this package along with the relevant plotting and summary functions.

Install Instructions

The avar package is available on both CRAN and GitHub. The CRAN version is considered stable while the GitHub version is subject to modifications/updates which may lead to installation problems or broken functions. You can install the stable version of the avar package with:

install.packages("avar")

For users who are interested in having the latest developments, the GitHub version is ideal although more dependencies are required to run a stable version of the package. Most importantly, users must have a (C++) compiler installed on their machine that is compatible with R (e.g. Clang). Once you’ve made sure that you have a compatible C++ compiler installed on your computer, run the following code in an R session and you will be ready to use the devlopment version of avar.

# Install dependencies
install.packages(c("devtools"))

# Install/Update the package from GitHub
devtools::install_github("SMAC-Group/avar")

# Install the package with Vignettes/User Guides 
devtools::install_github("SMAC-Group/avar", build_vignettes = TRUE)

References

Allan, David W. 1966. “Statistics of Atomic Frequency Standards.” Proceedings of the IEEE 54 (2): 221–30.

Guerrier, Stéphane, Roberto Molinari, and Yannick Stebler. 2016. “Theoretical Limitations of Allan Variance-Based Regression for Time Series Model Estimation.” IEEE Signal Processing Letters 23 (5): 597–601.

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Version

Install

install.packages('avar')

Monthly Downloads

317

Version

0.1.3

License

AGPL-3

Issues

Pull Requests

Stars

Forks

Maintainer

St<c3><a9>phane Guerrier

Last Published

August 29th, 2023

Functions in avar (0.1.3)

print.avar

Prints Allan Variance
covmat_bi

Calculate Theoretical Covariance Matrix of Bias-Instability Process
plot.imu_avlr

Plot the AVLR with the Allan Deviation for IMU
summary.avar

Summary Allan Variance
covmat_nswn

Calculate Theoretical Covariance Matrix of Non-Stationary White Noise Process
plot.imu_avar

Plot Allan Variance based on IMU Data
print.imu_avlr

Print imu_avlr object
covmat_ar1blocks

Calculate Theoretical Covariance Matrix of AR(1) Blocks Process
imar_av

Allan variance of IMU Data from IMAR Gyroscopes
ln200_av

Allan variance of IMU Data from a LN200 sensor
navchip_av

Allan variance of IMU Data from a navchip sensor
plot.avlr

Plot the AVLR with the Allan Variance
plot.avar

Plot Allan Deviation
print.avlr

Print avlr object
adis_av

Allan variance of IMU Data from an ADIS 16405 sensor
av_rw

Calculate Theoretical Allan Variance for Random Walk Process
av_dr

Calculate Theoretical Allan Variance for Drift Process
av_qn

Calculate Theoretical Allan Variance for Stationary Quantization Noise Process
MOAV

Non-stationary Maximal-overlapping Allan Variance
av_ar1

Calculate Theoretical Allan Variance for Stationary First-Order Autoregressive (AR1) Process
av_wn

Calculate Theoretical Allan Variance for Stationary White Noise Process
NOAV

Non-stationary Non-overlapping Allan Variance
avar

Compute the Empirical Allan Variance
avar_mo_cpp

Compute Maximal-Overlap Allan Variance using Means
is.whole

Integer Check
boostrap_ci_avlr

Compute bootstrap confidence intervals for the AVLR estimator
kvh1750_av

Allan variance of IMU Data from a KVH1750 IMU sensor
fit_avlr

Internal function to the Allan Variance Linear Regression estimator
avlr

Computes the Allan Variance Linear Regression estimator
avar_to_cpp

Compute Tau-Overlap Allan Variance