ukf.update: Predict the state for the unscented Kalman Filter
In squipbar/filters: A package to compute (nonlinear) filters
Description
Usage
Arguments
Value
Description
Predict the state for the unscented Kalman Filter
Usage
1
2
ukf.update(m, P, g, R, y, n = length(m), alpha = 0.001, kappa = 0,
betta = 2)
Arguments
m
The predicted mean
P
The predicted covariance
g
The measurement equation
R
The measurement covariance
n
The dimension of the problem
Value
The mean and covariance of the predicted state
squipbar/filters documentation built on May 30, 2019, 8:41 a.m.
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Description Usage Arguments Value
Description
Predict the state for the unscented Kalman Filter
Usage
1 2 | ukf.update(m, P, g, R, y, n = length(m), alpha = 0.001, kappa = 0,
betta = 2)
|
Arguments
m |
The predicted mean |
P |
The predicted covariance |
g |
The measurement equation |
R |
The measurement covariance |
n |
The dimension of the problem |
Value
The mean and covariance of the predicted state
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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