outliers.effects
(Package: tsoutliers) :
Create the Pattern of Different Types of Outliers
These functions create a unit or weighted impulse for the five types of outliers considered in the package.
● Data Source:
CranContrib
● Keywords: ts
● Alias: outliers.effects
●
0 images
|
|
This function creates regressor variables for trading day, Easter and leap year effects over the sample period where the input time series is sampled.
● Data Source:
CranContrib
● Keywords: ts
● Alias: calendar.effects
●
0 images
|
outliers.regressors
(Package: tsoutliers) :
Regressor Variables for the Detection of Outliers
These functions create regressor variables to be used included in the regression where tests for presence will be applied.
● Data Source:
CranContrib
● Keywords: ts
● Alias: outliers.regressors
●
0 images
|
remove.outliers
(Package: tsoutliers) :
Stage II of the Procedure: Remove Outliers
This functions tests for the significance of a given set of outliers in a time series model that is fitted including the outliers as regressor variables.
● Data Source:
CranContrib
● Keywords: ts
● Alias: remove.outliers
●
0 images
|
|
This function applies the test for normality proposed in Jarque and Bera (1980).
● Data Source:
CranContrib
● Keywords: ts, htest
● Alias: JarqueBera.test, print.mhtest
●
0 images
|
outliers
(Package: tsoutliers) :
Define Outliers in a Data Frame
This function is an interface to create a data frame defining the type, observation and weight of outliers. The output is properly designed to be used as input to other functions such as outliers.effects and outliers.regressors.
● Data Source:
CranContrib
● Keywords: ts
● Alias: outliers
●
0 images
|
outliers.tstatistics
(Package: tsoutliers) :
Test Statistics for the Significance of Outliers
This function computes the t-statistics to assess the significance of different types of outliers at every possible time point. The statistics can be based either on an ARIMA model, arima, auto.arima, or a structural time series model, stsmFit.
● Data Source:
CranContrib
● Keywords: ts
● Alias: outliers.tstatistics
●
0 images
|
locate.outliers.loops
(Package: tsoutliers) :
Stage I of the Procedure: Locate Outliers (Loop Around Functions)
These functions implement the inner and outer loops based of the procedure to locate outliers following the approach described in Chen and Liu (1993) .
● Data Source:
CranContrib
● Keywords: ts
● Alias: locate.outliers.iloop, locate.outliers.oloop
●
0 images
|
coefs2poly
(Package: tsoutliers) :
Product of the Polynomials in an ARIMA Model
This function collapses the polynomials of an ARIMA model into two polynomials: the product of the autoregressive polynomials and the product of the moving average polynomials.
● Data Source:
CranContrib
● Keywords: ts, math, symbolmath
● Alias: coefs2poly
●
0 images
|
tsoutliers-package
(Package: tsoutliers) :
Automatic Detection of Outliers in Time Series
This package implements a procedure based on the approach described in Chen and Liu (1993) for automatic detection of outliers in time series. Innovational outliers, additive outliers, level shifts, temporary changes and seasonal level shifts are considered.
● Data Source:
CranContrib
● Keywords: package, ts
● Alias: tsouliers-package
●
0 images
|
providing 
.