avlr {avar} | R Documentation |
Computes the Allan Variance Linear Regression estimator
Description
Estimate the parameters of time series models based on the Allan Variance Linear Regression (AVLR) approach
Usage
avlr(x, ...)
## Default S3 method:
avlr(
x,
qn = NULL,
wn = NULL,
rw = NULL,
dr = NULL,
ci = FALSE,
B = 100,
alpha = 0.05,
...
)
## S3 method for class 'imu_avar'
avlr(
x,
qn_gyro = NULL,
wn_gyro = NULL,
rw_gyro = NULL,
dr_gyro = NULL,
qn_acc = NULL,
wn_acc = NULL,
rw_acc = NULL,
dr_acc = NULL,
B = 100,
alpha = 0.05,
...
)
Arguments
x |
A |
... |
Further arguments passed to other methods. |
qn |
A |
wn |
A |
rw |
A |
dr |
A |
ci |
A |
B |
A |
alpha |
A |
qn_gyro |
A |
wn_gyro |
A |
rw_gyro |
A |
dr_gyro |
A |
qn_acc |
A |
wn_acc |
A |
rw_acc |
A |
dr_acc |
A |
Value
If the input x
is a vec
, then the function returns a list
that contains:
"estimates": The estimated value of the parameters.
"implied_ad": The Allan deviation implied by the estimated parameters.
"implied_ad_decomp": The Allan deviation implied by the estimated parameters for each individual model (if more than one is specified).
"av": The
avar
object computed from the provided data.
If the input x
is of the class imu_avar
, then the function returns a list
that contains:
"gyro": The estimation results correseponding to the gyroscope component.
"acc": The estimation results correseponding to the accelerometer component.
"imu_av": The
imu_avar
object computed based on the IMU data.
Examples
set.seed(999)
N = 100000
Xt = rnorm(N) + cumsum(rnorm(N, 0, 3e-3))
av = avar(Xt)
plot(av)
# Input time series
fit = avlr(Xt, wn = 1:8, rw = 11:15)
fit
# Input directly Allan variance
fit = avlr(av, wn = 1:8, rw = 11:15)
fit
# Plot functions
plot(fit)
plot(fit, decomp = TRUE)
plot(fit, decomp = TRUE, show_scales = TRUE)