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Resource Library
Time Series and Seasonal Adjustment Working Papers
Time Series and Seasonal Adjustment Working Papers
The following papers of interest to researchers and seasonal adjustment experts are available for downloading.
Working Paper
A Nonparametric Method for Asymmetrically Extending Signal Extracti...
A Nonparametric Method for Asymmetrically Extending Signal Extraction Filters
Working Paper
Goodness-of-Fit and Badness-of-Fit Diagnostic Tests for Time Series...
Goodness-of-Fit and Badness-of-Fit Diagnostic Tests for Time Series Models
Working Paper
A Bayesian Approach to Estimating the Long Memory Parameter
A Bayesian Approach to Estimating the Long Memory Parameter
Working Paper
New ARIMA Models for Seasonal Time Series and Their Application to ...
New ARIMA Models for Seasonal Time Series and Their Application to Seasonal Adjustment and Forecasting
Working Paper
A Mean Squared Error Criterion for Comparing X-12-ARIMA and Model-B...
A Mean Squared Error Criterion for Comparing X-12-ARIMA and Model-Based Seasonal Adjustment Filters
Working Paper
Coherent Trends, Turning Points, and Forecasts for ACS Data
Coherent Trends, Turning Points, and Forecasts for ACS Data
Working Paper
Release Notes for Version 0.3 of X-12-ARIMA
Release Notes for Version 0.3 of X-12-ARIMA
Working Paper
Semiparametric Tail Index Estimation: A Density Quantile Approach
Semiparametric Tail Index Estimation: A Density Quantile Approach
Working Paper
Tail Index Estimation for Parametric Families Using Log Moments
Tail Index Estimation for Parametric Families Using Log Moments
Working Paper
Comparing Automatic Modeling Procedures of TRAMO and X-12-ARIMA
The U.S. Census Bureau's enhanced X-12-ARIMA seasonal adjustment program includes the automatic ARIMA model selection procedure developed by Statistics Canada.
Working Paper
Determining Seasonality: A Comparison of Diagnostics From X-12-ARIMA
Before a series is seasonally adjusted, it should be shown that the series is seasonal.
Working Paper
Issues in Modeling & Adjusting Effects in Economic Time Series
The effectiveness of alternate models for estimating trading day and moving holiday effects in economic time series are examined.
Working Paper
Optimality of GLS for One-Step-Ahead Forecasting of regARIMA
We consider the modeling of a time series described by a linear regression component whose regressor sequence satisfies the generalized asymptotic sample.
Page Last Revised - November 22, 2021
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