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Forecasting with Exponential Smoothing: The State Space Approach

1. Aufl., 2008

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A state space framework for automatic forecasting using exponential smoothing methods

International journal of forecasting, 2002-07, Vol.18 (3), p.439-454

2002

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Forecasting compositional time series: A state space approach

International journal of forecasting, 2017-04, Vol.33 (2), p.502-512

2017

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Forecasting Time Series With Complex Seasonal Patterns Using Exponential Smoothing

Journal of the American Statistical Association, 2011-12, Vol.106 (496), p.1513-1527

2011

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Forecasting intraday time series with multiple seasonal cycles using parsimonious seasonal exponential smoothing

Omega (Oxford), 2012-12, Vol.40 (6), p.748-757

2012

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Forecasting the intermittent demand for slow-moving inventories: A modelling approach

International journal of forecasting, 2012-04, Vol.28 (2), p.485-496

2012

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Forecasting time series with multiple seasonal patterns

European journal of operational research, 2008-11, Vol.191 (1), p.207-222

2008

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Exponential smoothing model selection for forecasting

International journal of forecasting, 2006-04, Vol.22 (2), p.239-247

2006

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A study of outliers in the exponential smoothing approach to forecasting

International journal of forecasting, 2012-04, Vol.28 (2), p.477-484

2012

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Incorporating a tracking signal into a state space model

International journal of forecasting, 2009-07, Vol.25 (3), p.526-530

2009

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Prediction intervals for exponential smoothing using two new classes of state space models

Journal of forecasting, 2005-01, Vol.24 (1), p.17-37

2005

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Exponential smoothing models: Means and variances for lead-time demand

European journal of operational research, 2004-10, Vol.158 (2), p.444-455

2004

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Forecasting models and prediction intervals for the multiplicative Holt–Winters method

International journal of forecasting, 2001-04, Vol.17 (2), p.269-286

2001

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Monitoring processes with changing variances

International journal of forecasting, 2009-07, Vol.25 (3), p.518-525

2009

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Feasible parameter regions for alternative discrete state space models

Statistics & probability letters, 2008-12, Vol.78 (17), p.2963-2970

2008

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Forecasting for inventory control with exponential smoothing

International journal of forecasting, 2002-01, Vol.18 (1), p.5-18

2002

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Forecasting intraday time series with multiple seasonal cycles using parsimonious seasonal exponential smoothing : Forecasting in Management Science

Omega (Oxford), 2012, Vol.40 (6), p.748-757

2012

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A New Look at Models For Exponential Smoothing

Journal of the Royal Statistical Society. Series D (The Statistician), 2001-01, Vol.50 (2), p.147-159

2001

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Prediction Intervals for ARIMA Models

Journal of business & economic statistics, 2001-04, Vol.19 (2), p.217-225

2001

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Reconstructing the Kalman Filter for Stationary and Non Stationary Time Series

Studies in Nonlinear Dynamics & Econometrics, 2003-07, Vol.7 (2), p.1

2003

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Exponential smoothing of seasonal data: a comparison

Journal of forecasting, 2001-04, Vol.20 (3), p.197-202

2001

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Estimation and Prediction for a Class of Dynamic Nonlinear Statistical Models

Journal of the American Statistical Association, 1997-12, Vol.92 (440), p.1621-1629

1997

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Trends, lead times and forecasting

International journal of forecasting, 1997-12, Vol.13 (4), p.477-488

1997

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INITIALIZATION OF THE KALMAN FILTER WITH PARTIALLY DIFFUSE INITIAL CONDITIONS

Journal of time series analysis, 1996-07, Vol.17 (4), p.409-424

1996

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Forecasting time series with multiple seasonal patterns

European journal of operational research, 2008-11, Vol.191 (1), p.205

2008

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Forecasting with Exponential Smoothing: The State Space Approach

A state space framework for automatic forecasting using exponential smoothing methods

Forecasting compositional time series: A state space approach

Forecasting Time Series With Complex Seasonal Patterns Using Exponential Smoothing

Forecasting intraday time series with multiple seasonal cycles using parsimonious seasonal exponential smoothing

Forecasting the intermittent demand for slow-moving inventories: A modelling approach

Forecasting time series with multiple seasonal patterns

Exponential smoothing model selection for forecasting

A study of outliers in the exponential smoothing approach to forecasting

Incorporating a tracking signal into a state space model

Prediction intervals for exponential smoothing using two new classes of state space models

Exponential smoothing models: Means and variances for lead-time demand

Forecasting models and prediction intervals for the multiplicative Holt–Winters method

Monitoring processes with changing variances

Feasible parameter regions for alternative discrete state space models

Forecasting for inventory control with exponential smoothing

Forecasting intraday time series with multiple seasonal cycles using parsimonious seasonal exponential smoothing : Forecasting in Management Science

A New Look at Models For Exponential Smoothing

Prediction Intervals for ARIMA Models

Reconstructing the Kalman Filter for Stationary and Non Stationary Time Series

Exponential smoothing of seasonal data: a comparison

Estimation and Prediction for a Class of Dynamic Nonlinear Statistical Models

Trends, lead times and forecasting

INITIALIZATION OF THE KALMAN FILTER WITH PARTIALLY DIFFUSE INITIAL CONDITIONS

Forecasting time series with multiple seasonal patterns

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