census.gov Notification
Due to the lapse of federal funding, portions of this website are not being updated. Any inquiries submitted via www.census.gov will not be answered until appropriations are enacted.

Asymptotic Stationarity Properties of Out-of-Sample Forecast Errors of Misspecifed RegARIMA Models

Skip Navigation
Within Library

Asymptotic Stationarity Properties of Out-of-Sample Forecast Errors of Misspecifed RegARIMA Models

Written by:

Introduction

Asymptotic Stationarity Properties of Out-of-Sample Forecast Errors of Misspecified RegARIMA Models
Download Asymptotic Stationarity Properties of Out-of-Sample Forecast Errors of Misspecified RegARIMA Models [PDF - <1.0 MB]

Suppose we have observations of a time series of the form where is a sequence of nonstochastic column vectors and is a mean zero process whose autocovariance structure is stationary or asymptotically stationary in a sense to be defined. With monthly or quarterly economic data for example, the regressor sequence might describe holiday effects.

Others in Series

Working Paper
A Set of Quality Control Statistics for the X-11-ARIMA
October 01, 1978
The X-11 Variant of the Census Method II Seasonal Adjustment Method contained a summary measures table denoted by F.2.
Working Paper
An Empirical Evaluation of the Performance of TRAMO/SEATS
October 01, 2000
TRAMO and SEATS are linked programs developed by Victor Gomez and Agustin Maravall to seasonally adjust time series.
Working Paper
Comparison of Time Series Characteristics for Seasonal Adjustments
October 01, 2002
This paper shows examples of why the diagnostics in X-12-SEATS are very useful.
View All
Page Last Revised - October 8, 2021