GetResiduals

This utility function is useful to use in the portmanteau functions,
BoxPierce, MahdiMcLeod, Hosking, LiMcLeod, LjungBox, and portest.
GetResiduals() function takes a fitted time-series object with class "ar",
"arima0", "Arima", ("ARIMA forecast ARIMA Arima"), "lm", ("glm" "lm"),
"varest", or "list". and returns the residuals and the order from the fitted
object.
This method and the bottom documentation is taken directly from the original
'portes' package.

Opinionated functions that enable easier and faster
analysis of Viva Insights data. There are three main types of functions in 'wpa':
(i) Standard functions create a 'ggplot' visual or a summary table based on a specific
Viva Insights metric; (2) Report Generation functions generate HTML reports on
a specific analysis area, e.g. Collaboration; (3) Other miscellaneous functions cover
more specific applications (e.g. Subject Line text mining) of Viva Insights data.
This package adheres to 'tidyverse' principles and works well with the pipe syntax.
'wpa' is built with the beginner-to-intermediate R users in mind, and is optimised for
simplicity.

Martin Chan

Tools for Analysing and Visualising Viva Insights Data

Carlos Morales

Mark Powers

Ainize Cidoncha

Rosamary Ochoa Vargas

Tannaz Sattari

Lucas Hogner

Jasminder Thind

Simone Liebal

Aleksey Ashikhmin

Ellen Trinklein

Microsoft Corporation 

GetResiduals function

<dl><dt>obj</dt>
<dd>a fitted time-series model with class "ar", "arima0", "Arima",
("ARIMA forecast ARIMA Arima"), "lm", ("glm" "lm"), "varest", or "list".</dd></dl>

Arguments

Author

Extract Residuals from ARIMA, VAR, or any Simulated Fitted Time Series Model — GetResiduals

<dl>

<dt>obj</dt>
<dd>a fitted time-series model with class "ar", "arima0", "Arima",
("ARIMA forecast ARIMA Arima"), "lm", ("glm" "lm"), "varest", or "list".</dd>

</dl>

Extract Residuals from ARIMA, VAR, or any Simulated Fitted Time Series Model

GetResiduals: Extract Residuals from ARIMA, VAR, or any Simulated Fitted Time Series Model

Description

Usage

Value

Arguments

Author

Examples