[PDF] Top 20 Judgmental Selection of Forecasting Models
Has 10000 "Judgmental Selection of Forecasting Models" found on our website. Below are the top 20 most common "Judgmental Selection of Forecasting Models".
Judgmental Selection of Forecasting Models
... in judgmental forecasting tasks, especially for fore- casts that involve trends, seasonality and/or the effect of special events such as ...of judgmental forecasting under ...cing ... See full document
13
Evaluation of Accuracy in Identification of ARIMA Models Based on Model Selection Criteria for Inflation Forecasting with the TSClust Approach
... model selection criteria to choose the best ARIMA ...model selection criteria can produce the best ARIMA models that are different so it can be difficult to choose the best model to be ...model ... See full document
5
Forecasting irish inflation using ARIMA models
... Once a model or selection of models has been chosen, the models should then be used to forecast the time series, preferably using out-of-sample data to evaluate the forecasting performan[r] ... See full document
49
Oil Price Forecasting Based on Various Univariate Time Series Models
... time-series models were investigated: ES, HW and ...given models with actual ...HW models. The six selection criteria used to quantify the qualities of the forecasts yielded their smallest ... See full document
10
On the Selection of Common Factors for Macroeconomic Forecasting
... Bai and Ng (2009) proposed componentwise and block-wise boosting algorithms for isolating the predictors in FAR models that are most helpful in predicting a variable of interest. The algo- rithms do not rely on ... See full document
31
Dynamic staged trees for discrete multivariate time series : forecasting, model selection and causal analysis
... graphical models developed for event history analysis are local independence graphs (Didelez 2008) and graphical duration graphs (Gottard ...tree models of the type described here and event history ... See full document
29
Optimal Forecasting of Noncausal Autoregressive Time Series
... reestimated models at each step with the estimation sample always starting from the …rst quarter of ...AR models as well as the AR(1,4) model selected for the entire sample in Section 4 are ...model ... See full document
31
Selection of Heteroscedastic Models: A Time Series Forecasting Approach
... model selection, this study adopted out-of-sample model selection approach for selecting models with improved forecasting accuracies and ...out-of-sample forecasting performance evalua- ... See full document
16
Identification and forecasting in mortality models
... a selection effect for the assured ...to forecasting the extrapolative method appears to depend on the ad hoc identified parameter as well as the ... See full document
25
Modelling and forecasting volatility of East Asian Newly Industrialized Countries and Japan stock markets with non linear models
... GARCH models generate lower RMSEs and MAEs than asymmetric ...asymmetric models are superior to GARCH models in forecasting Taiwan stock market volatility with model selections based on the ... See full document
23
Evaluating Density Forecasting Models
... A common application for evaluation techniques is model selection. Here, the goal is to determine the best model set up to use for your final prediction model. In this sim- ple example we show how it is useful to ... See full document
12
Selection of mathematical modelling for forecasting of rice production in Assam, India
... and Selection of Appropriate Model: In this study several regressions models will be done for each proposed models to select an appropriate ...fixed models will be used (Kumar et ... See full document
5
Bayesian Model Selection and Forecasting in Noncausal Autoregressive Models
... model selection criterion and yields information on the probabilities of the alternative causal and noncausal ...AR models allowing for dependence on past ...alternative models especially at longer ... See full document
32
On the accuracy of judgmental interventions on forecasting support systems
... that judgmental interventions can be effective when applied to SKU data comes from Mathews and Diamantopoulos with a series of contributions (1992, 1990, 1989, 1986) showing that judgmental “revision” ... See full document
27
Model selection, estimation and forecasting in INAR(p) models: A likelihood-based Markov Chain approach
... series models is to use conditional expectations as this technique will yield forecasts with minimum mean squared forecast ...data models. This paper presents a method of coherent forecasting for ... See full document
22
Using a rolling training approach to improve judgmental extrapolations elicited from forecasters with technical knowledge
... model selection (Fildes and Petropoulos, ...window) forecasting procedure with updating every h periods, where the observation window is not kept constant but increases with the sample ... See full document
23
Sentiment indicators and macroeconomic data as drivers for low frequency stock market volatility
... GARCH models for stock return volatility, where the low-frequency compo- nent of volatility is driven by macroeconomic variables, have recently provided robust links between the macroeconomy and stock market ... See full document
49
Data driven retail food waste reduction : a comparison of demand forecasting techniques and dynamic pricing strategies
... advanced forecasting techniques perform relatively ...these models can extract more complex patterns in weekly sales ...different selection of techniques to implement. Again, in all ... See full document
105
Forecasting Performances of GARCH Families of Models
... twelve models with various specifications of GARCH, EGARCH and GJR-GARCH has been estimated for closing return series of nifty till 31 st May, ...the forecasting performance of the different GARCH family of ... See full document
7
Recent advances in flood forecasting and flood risk assessment
... parametric models, whose parameters may be estimated and updated continuously through ...the models as a priori knowledge, to reduce uncertainty and improve the reproduction of physical phenomena beyond the ... See full document
5
Related subjects