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A new forecasting approach for the hospitality industry
16 references·3 citing·30 second hop
A new forecasting approach for the hospitality industry (2015)A new forecasting approach for the hospit…Tourism demand modelling and forecasting—A review of recent research (2007)Tourism demand modelling and …Support vector regression with genetic algorithms in forecasting tourism demand (2006)Support vector regression wit…Revenue Management Under a General Discrete Choice Model of Consumer Behavior (2004)Revenue Management Under a Ge…Neural network forecasting for seasonal and trend time series (2003)Neural network forecasting fo…Tourism as a long-run economic growth factor: the Spanish case (2002)Tourism as a long-run economi…Back-propagation learning in improving the accuracy of neural network-based tourism demand forecasting (2000)Back-propagation learning in …Numerical distribution functions of likelihood ratio tests for cointegration (1999)Numerical distribution functi…Forecasting with artificial neural networks: (1998)Forecasting with artificial n…Comparing Predictive Accuracy (1995)Comparing Predictive AccuracyComparing Predictive Accuracy (1994)Comparing Predictive AccuracyTesting the null hypothesis of stationarity against the alternative of a unit root (1992)Testing the null hypothesis o…Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models (1991)Estimation and Hypothesis Tes…Testing for a Unit Root in Time Series Regression (1988)Testing for a Unit Root in Ti…Statistical analysis of cointegration vectors (1988)Statistical analysis of coint…Distribution of the Estimators for Autoregressive Time Series With a Unit Root (1979)Distribution of the Estimator…Distribution of the Estimators for Autoregressive Time Series with a Unit Root (1979)Distribution of the Estimator…Modeling and Forecasting Daily Hotel Demand: A Comparison Based on SARIMAX, Neural Networks, and GARCH Models (2021)Modeling and Forecasting Dail…A new metric of consensus for Likert-type scale questionnaires: an application to consumer expectations (2021)A new metric of consensus for…From travel agents to OTAs: How the evolution of consumer booking behavior has affected revenue management (2016)From travel agents to OTAs: H…Time Series Analysis: Forecasting and Control (1977)Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation (1982)Managerial Applications of Neural Networks: The Case of Bank Failure Predictions (1992)Financial time series forecasting using support vector machines (2003)Time series forecasting using a hybrid ARIMA and neural network model (2003)DeepAR: Probabilistic forecasting with autoregressive recurrent networks (2019)Co-Integration and Error Correction: Representation, Estimation, and Testing (1987)MAXIMUM LIKELIHOOD ESTIMATION AND INFERENCE ON COINTEGRATION — WITH APPLICATIONS TO THE DEMAND FOR MONEY (1990)Oil prices, inflation and interest rates in a structural cointegrated VAR model for the G-7 countries (2007)CO2 emissions, electricity consumption and output in ASEAN (2010)The contribution of foreign direct investment to clean energy use, carbon emissions and economic growth (2013)A Monetary History of the United States 1867-1960 (1964)Time Series Analysis Forecasting and Control. (1971)Bounds testing approaches to the analysis of level relationships (2001)A Note with Quantiles of the Asymptotic Distribution of the Maximum Likelihood Cointegration Rank Test Statistics1 (1992)Unit root tests in panel data: asymptotic and finite-sample properties (2002)Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root (1981)Trends and random walks in macroeconmic time series (1982)A simple panel unit root test in the presence of cross‐section dependence (2007)A Comparative Study of Unit Root Tests with Panel Data and a New Simple Test (1999)Unit root tests for panel data (2001)Modelling Asymmetric Cointegration and Dynamic Multipliers in a Nonlinear ARDL Framework (2014)PANEL COINTEGRATION: ASYMPTOTIC AND FINITE SAMPLE PROPERTIES OF POOLED TIME SERIES TESTS WITH AN APPLICATION TO THE PPP HYPOTHESIS (2004)Answering the Skeptics: Yes, Standard Volatility Models do Provide Accurate Forecasts (1998)A Comprehensive Look at The Empirical Performance of Equity Premium Prediction (2007)Strictly Proper Scoring Rules, Prediction, and Estimation (2007)Testing for unit roots in heterogeneous panels (2003)Testing the equality of prediction mean squared errors (1997)Consumption, Aggregate Wealth, and Expected Stock Returns (2001)Deep learning with long short-term memory networks for financial market predictions (2017)
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References

  • 1979Distribution of the Estimators for Autoregressive Time Series with a Unit Root23,183 cited
  • 1988Testing for a Unit Root in Time Series Regression19,288 cited
  • 1988Statistical analysis of cointegration vectors17,038 cited
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  • 1991Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models11,146 cited
  • 1979Distribution of the Estimators for Autoregressive Time Series With a Unit Root9,128 cited
  • 1994Comparing Predictive Accuracy5,495 cited
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  • 1999Numerical distribution functions of likelihood ratio tests for cointegration2,028 cited
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  • 2007Tourism demand modelling and forecasting—A review of recent research1,419 cited
  • 2004Revenue Management Under a General Discrete Choice Model of Consumer Behavior1,110 cited
  • 2003Neural network forecasting for seasonal and trend time series987 cited
  • 2006Support vector regression with genetic algorithms in forecasting tourism demand

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378 cited
  • 2000Back-propagation learning in improving the accuracy of neural network-based tourism demand forecasting344 cited
  • Cited by

    • 2021Modeling and Forecasting Daily Hotel Demand: A Comparison Based on SARIMAX, Neural Networks, and GARCH Models63 cited
    • 2016From travel agents to OTAs: How the evolution of consumer booking behavior has affected revenue management35 cited
    • 2021A new metric of consensus for Likert-type scale questionnaires: an application to consumer expectations23 cited