Pronóstico de la demanda turística de Chile basado en modelos lineales y no lineales estacionales

TIn this paper, the Chilean tourism demand experienced during period 2000?2018 has been modelled using a linear regression model with dichotomous variables (MRL) and an ARIMA seasonal component (SARIMA). The results show that SARIMA approach is more effective in replicating non?stationary, non?linear behaviour presence of seasonality series, forecasts obtained from presenting low rate error, case ?5.6% for outbound ?5.9% inbound tourism. In consequence, may be tool forecasting forecast short term, support planning management sector face fluctuations demand.