战后斯里兰卡国际旅游收入预测的林对数模型

K.M.U.B Konarasinghe
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引用次数: 1

摘要

收入预测在任何企业的计划和其他决策过程中都是必不可少的。拟合一个合适的林对数模型来预测斯里兰卡的国际旅游收入是本研究的目的。月收入数据为2009年1月至2013年12月。数据来自斯里兰卡旅游发展局的年度报告。采用对数变换的自回归分布滞后模型(Lin-Log模型)对不同滞后情况下的收益预测进行了检验。整体模型检验采用单因素方差分析(ANOVA)技术,单项参数检验采用t检验。残差图和残差的Anderson-Darling检验和Durbin-Watson检验作为模型验证标准。通过考虑调整后的R2和三个误差测量来评估模型的预测能力。箱形图和须状图显示数据集中没有异常值。结果表明,林对数模型在滞后1、滞后2和滞后3处具有显著性。模型拟合和验证时的MAPE分别为14.86%和16.63%。模型校正后的R2为83.6%。残差图和Anderson-Darling检验证实了残差的正态性。残差Vs拟合也证实了残差的独立性。Durbin-Watson的数据也证实了这一点。结果表明,林对数模型适用于斯里兰卡国际旅游收入的预测。建议在预测斯里兰卡的国际旅游收入时也测试自动回归综合移动平均(ARIMA)模型。
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Lin-Log Model for Forecasting International Tourism Income in Sri Lanka: Post-War Period
Income forecasting is an essential discipline in planning and other decision-making processes within any business. Fitting a suitable Lin-log model for forecasting international tourism income in Sri Lanka is the objective of the study. Monthly income data utilized from January 2009 to December 2013. Data obtained from annual reports of Sri Lanka Tourism Development Authority. Autoregressive Distributed Lag Model with log transformation (Lin-Log Model) was tested on forecasting income at different lags. One way Analysis of Variance (ANOVA) technique was used for overall model testing and t-test was used for individual parameter testing. Residual plots and Anderson-Darling test for residuals and the Durbin-Watson test was used as a model validation criterion. Forecasting ability of the models was assessed by considering adjusted R2 and three measurements of errors. Box and whisker plot showed no outliers in the data set. Results revealed that Lin-log model was significant at lag 1, 2 and 3. MAPE’s of the model in model fitting and verification were 14.86% and 16.63% respectively. Adjusted R2 of the model was 83.6 %. Residual plots and Anderson-Darling tests confirmed the normality of residuals. Also, residuals Vs fits confirmed the independence of residuals. Durbin-Watson statistic confirms the same. It was concluded that the Lin- log model is suitable for forecasting international tourism income in Sri Lanka. It is recommended to test Auto Regressive Integrated Moving Average (ARIMA) models also on forecasting international tourism income in Sri Lanka.
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