The Holt-Winters Forecasting Procedure

Chatfield, Chris

doi:10.2307/2347162

Cited by 289 publications

(178 citation statements)

References 19 publications

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“…The Holt-Winters seasonal model based on the addition is added to the horizontal component and the seasonal component [12]. The complete definition of the model is as follows: …”

Section: Holt-winters Modelmentioning

confidence: 99%

Short-term Forecast Model of Vehicles Volume Based on ARIMA Seasonal Model and Holt-Winters

Wang¹,

et al. 2017

ITM Web Conf.

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Abstract:In order to alleviate the urban traffic congestion and ensure traffic safety, we need to do a good job in urban road traffic safety planning, make the real-time analysis and forecast of urban traffic flow to detect changes of current traffic flow in time, make scientific planning of roads and improve the road service ability and the transport efficiency of freight vehicles. The data of short-term vehicles volume is characterized by uncertainty and timing correlation series. Given this, the ARIMA seasonal model and the Holt-Winters model are used to establish a forecasting model for the short-term vehicles volume of the city. Finally, we compare the model with predictions.

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“…The Holt-Winters seasonal model based on the addition is added to the horizontal component and the seasonal component [12]. The complete definition of the model is as follows: …”

Section: Holt-winters Modelmentioning

confidence: 99%

Short-term Forecast Model of Vehicles Volume Based on ARIMA Seasonal Model and Holt-Winters

Wang¹,

et al. 2017

ITM Web Conf.

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“…The model was first proposed in the early 1960s and applies three exponential smoothing formulae to the series, respectively to the mean, trend, and each seasonal sub-series (Chatfield, 1978) [15].…”

Section: The Holt-winters Model (Hw)mentioning

confidence: 99%

“…For an application of the same methodology to predict water pollution in Eastern Europe see Paraschiv, Tudor, and Petrariu (2015) [16]. Additionally, see Chatfield [15] for a more in-depth overview of the Holt-Winters Model. The BATS and TBATS models, which are in the exponential-smoothing framework and are capable of handling multiple seasonalities as well as complex seasonalities were proposed by De Livera, Hyndman and Snyder (2011) [17].…”

Section: The Holt-winters Model (Hw)mentioning

confidence: 99%

Predicting the Evolution of CO2 Emissions in Bahrain with Automated Forecasting Methods

Tudor¹

2016

Sustainability

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Abstract:The 2012 Doha meeting established the continuation of the Kyoto protocol, the legally-binding global agreement under which signatory countries had agreed to reduce their carbon emissions. Contrary to this assumed obligation, all G20 countries with the exception of France and the UK saw significant increases in their CO 2 emissions over the last 25 years, surpassing 300% in the case of China. This paper attempts to forecast the evolution of carbon dioxide emissions in Bahrain over the 2012-2021 decade by employing seven Automated Forecasting Methods, including the exponential smoothing state space model (ETS), the Holt-Winters Model, the BATS/TBATS model, ARIMA, the structural time series model (STS), the naive model, and the neural network time series forecasting method (NNAR). Results indicate a reversal of the current decreasing trend of pollution in the country, with a point estimate of 2309 metric tons per capita at the end of 2020 and 2317 at the end of 2021, as compared to the 1934 level achieved in 2010. The country's baseline level corresponding to year 1990 (as specified by the Doha amendment of the Kyoto protocol) is approximately 25.54 metric tons per capita, which implies a maximum level of 20.96 metric tons per capita for the year 2020 (corresponding to a decrease of 18% relative to the baseline level) in order for Bahrain to comply with the protocol. Our results therefore suggest that Bahrain cannot meet its assumed target.

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“…Indeed, Chatfield (1978) Newbold and Bos (1989) point out, assertions in the literature about the choice of smoothing constants are often predicated upon erroneous assumptions about the probability process underlying the time series.…”

Section: Automatic Parameter Optimizationmentioning

confidence: 99%

“…Accordingly, if a time plot of the time series does not clearly indicate that the seasonal spread increases as the level of the series increases (the multiplicative pattern), the practitioner would be wise to compare the AMS forecast with one based on the additive seasonality option from the seasonal menu. For an example, see Chatfield (1978).…”

Section: Unified Frameworkmentioning

confidence: 99%

Automatic forecasting software: A survey and evaluation

Tashman

Leach

1991

International Journal of Forecasting

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Forecasting software, through the incorporation of automatic features for model selection and estimation, has made heretofore "complex" methods more accessible to the practitioner, giving rise concomitantly to claims that software now relieves the practitioner of the burden of technical knowledge. Academics, however, have questioned the wisdom of forecasting without foretraining. This paper presents a survey and evaluation of automatic forecasting, based on the features of thirteen forecasting packages which perform single-equation methods on time series data. Our goals are (a) to clarify for the practitioner the virtues and limitations of automatic forecasting, and (b) to assess whether the software encourages if not nurtures good forecasting practice in the identification, evaluation, and defense of a forecasting model. Our principal conclusions: forecasting software can provide substantial and reliable assistance to the practitioner in the selection of appropriate specifications for extrapolative models. With regard to important tasks involving the evaluation and presentation of forecasts, as well as for the determination of whether the introduction of causal variables is worthwhile, the practitioner is left largely to his own devices, expertise, and judgment. The serious danger to the untrained practitioner is the "closedworld" problem of knowing what you don't know.

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The Holt-Winters Forecasting Procedure

Cited by 289 publications

References 19 publications

Short-term Forecast Model of Vehicles Volume Based on ARIMA Seasonal Model and Holt-Winters

Short-term Forecast Model of Vehicles Volume Based on ARIMA Seasonal Model and Holt-Winters

Predicting the Evolution of CO2 Emissions in Bahrain with Automated Forecasting Methods

Automatic forecasting software: A survey and evaluation

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