lookout_ts: Identifies outliers in univariate time series using the...
In lookout: Leave One Out Kernel Density Estimates for Outlier Detection
lookout_ts R Documentation
Identifies outliers in univariate time series using the algorithm lookout.
Description
This is the time series implementation of lookout.
Usage
lookout_ts(x, alpha = 0.05)
Arguments
x
The input univariate time series.
alpha
The level of significance. Default is 0.05.
Value
A lookout object.
See Also
lookout
Examples
set.seed(1)
x <- arima.sim(list(order = c(1,1,0), ar = 0.8), n = 200)
x[50] <- x[50] + 10
plot(x)
lo <- lookout_ts(x)
lo
lookout documentation built on Oct. 14, 2022, 1:09 a.m.
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.
| lookout_ts | R Documentation |
Identifies outliers in univariate time series using the algorithm lookout.
Description
This is the time series implementation of lookout.
Usage
lookout_ts(x, alpha = 0.05)
Arguments
x |
The input univariate time series. |
alpha |
The level of significance. Default is |
Value
A lookout object.
See Also
lookout
Examples
set.seed(1) x <- arima.sim(list(order = c(1,1,0), ar = 0.8), n = 200) x[50] <- x[50] + 10 plot(x) lo <- lookout_ts(x) lo
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.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.