Forecasting Foreign Tourist Arrivals to India Using Time Series Models

Journal of Data Science

article

Shalini Chandra¹  Kriti Kumari¹ 

[1] Department of Mathematics and Statistics

关键词: Foreign tourist arrivals;    Time series models;    Forecast comparisons;   

DOI  :  10.6339/JDS.201810_16(4).00003

学科分类：土木及结构工程学

来源: JDS

【 摘 要 】

This study aims to compare various quantitative models to forecast monthly foreign tourist arrivals (FTAs) to India. The models which are considered here include vector error correction (VEC) model, Naive I and Naive II models, seasonal autoregressive integrated moving average (SARIMA) model and Grey models. A model based on combination of single forecast values using simple average (SA) method has also been applied. The forecasting performance of these models have been compared under mean absolute percentage error (MAPE) and U-statistic (Ustat) criteria. Empirical findings suggest that the combination model gives better forecast of FTAs to India relative to other individual time series models considered here.

【 授权许可】

CC BY