Search results for " smoothing"

Bayesian modeling of the evolution of male height in 18th century Finland from incomplete data.

2012

Abstract Data on army recruits’ height are frequently available and can be used to analyze the economics and welfare of the population in different periods of history. However, such data are not a random sample from the whole population at the time of interest, but instead is skewed since the short men were less likely to be recruited. In statistical terms this means that the data are left-truncated. Although truncation is well-understood in statistics a further complication is that the truncation threshold is not known, may vary from time to time, and auxiliary information on the threshold is not at our disposal. The advantage of the fully Bayesian approach presented here is that both the …

Bayesian forecasting with the Holt–Winters model

2010

Exponential smoothing methods are widely used as forecasting techniques in inventory systems and business planning, where reliable prediction intervals are also required for a large number of series. This paper describes a Bayesian forecasting approach based on the Holt–Winters model, which allows obtaining accurate prediction intervals. We show how to build them incorporating the uncertainty due to the smoothing unknowns using a linear heteroscedastic model. That linear formulation simplifies obtaining the posterior distribution on the unknowns; a random sample from such posterior, which is not analytical, is provided using an acceptance sampling procedure and a Monte Carlo approach gives …

Improving demand forecasting accuracy using nonlinear programming software

2006

We address the problem of forecasting real time series with a proportion of zero values and a great variability among the nonzero values. In order to calculate forecasts for a time series, the model coefficients must be estimated. The appropriate choice of values for the smoothing parameters in exponential smoothing methods relies on the minimization of the fitting errors of historical data. We adapt the generalized Holt–Winters formulation so that it can consider the starting values of the local components of level, trend and seasonality as decision variables of the nonlinear programming problem associated with this forecasting procedure. A spreadsheet model is used to solve the problems o…

A spreadsheet modeling approach to the Holt–Winters optimal forecasting

2001

Abstract The objective of this paper is to determine the optimal forecasting for the Holt–Winters exponential smoothing model using spreadsheet modeling. This forecasting procedure is especially useful for short-term forecasts for series of sales data or levels of demand for goods. The non-linear programming problem associated with this forecasting model is formulated and a spreadsheet model is used to solve the problem of optimization efficiently. Also, a spreadsheet makes it possible to work in parallel with various objective functions (measures of forecast errors) and different procedures for calculating the initial values of the components of the model. Using a scenario analysis, the se…

Forecasting correlated time series with exponential smoothing models

2011

Abstract This paper presents the Bayesian analysis of a general multivariate exponential smoothing model that allows us to forecast time series jointly, subject to correlated random disturbances. The general multivariate model, which can be formulated as a seemingly unrelated regression model, includes the previously studied homogeneous multivariate Holt-Winters’ model as a special case when all of the univariate series share a common structure. MCMC simulation techniques are required in order to approach the non-analytically tractable posterior distribution of the model parameters. The predictive distribution is then estimated using Monte Carlo integration. A Bayesian model selection crite…

Forecasting container transshipment in Germany

2009

International audience; In this paper, we examine container transshipment at German ports using the seasonal ARIMA (SARIMA) model and the Holt-Winters exponential smoothing approach. Our models are designed especially to take account of the seasonal behavior of the quarterly data used. We consider the dynamic development in this sector for the whole container throughput and also the destinations Asia, Europe and North America, which are the world's three main economic regions. Our data runs from the first quarter of 1989 to the fourth quarter of 2006. We provide detailed quarterly forecasts for the year 2007 and 2008. According to forecasting error measures such as Mean Square Error and The…

Adaptive P-splines via L1-type penalty in generalized additive models

2022

A Forecasting Support System Based on Exponential Smoothing

2010

This chapter presents a forecasting support system based on the exponential smoothing scheme to forecast time-series data. Exponential smoothing methods are simple to apply, which facilitates computation and considerably reduces data storage requirements. Consequently, they are widely used as forecasting techniques in inventory systems and business planning. After selecting the most adequate model to replicate patterns of the time series under study, the system provides accurate forecasts which can play decisive roles in organizational planning, budgeting and performance monitoring.

The appraisal smoothing in the real estate indeces

2013

The appraisal smoothing is the phenomenon in which the valuation of a property, based on the judgments of appraisers (expertise) rather than on the collection of market data, is influenced by previous valuations performed by the same expert. The most obvious consequence of the exercise of expertise is the tendency to generate in the time a smoothing in the estimated value. This is the first experimental application of the appraisal smoothing theory in Italy. The general spread of real estate valuations, based on prices and average prices refer to a single commercial parameter (usually the surface), generates the natural suspicion that the smoothing effect could be widely disseminated and th…

Noise Filtering Using Edge-Driven Adaptive Anisotropic Diffusion

2008

This paper presents a method aimed to noise removal in MRI (Magnetic Resonance Imaging). We propose an improvement of Perona and Malik's anisotropic diffusion filter. In our schema, the diffusion equation of the filter has been modified to take into account the edges direction, This allows the filter to blur uniform areas, while it better preserves the edges. Both quantitative and qualitative evaluation is presented and the results are compared with other methods.