Augmentation time series model with Kalman filter to predict foreign tourist arrivals in East Java

Seasonality in Tourism and Forecasting Foreign Tourist Arrivals in India

In the present age of globalization, technology-revolution and sustainable development, the presence of seasonality in tourist arrivals is considered as a key policy issue that affects the global tourism industry by creating instability in the demand and revenues. The seasonal component in a time-series distorts the prediction attempts for policy-making. In this context, it is quintessential to...

Forecasting tourist arrivals to Turkey

Modeling and forecasting techniques of the tourist arrivals are many and diverse. Th ere is no unique model that exactly outperforms the other models in every situation. Actually a few studies have realized modeling and forecasting the tourist arrivals to Turkey and these studies have not focused on the total tourist arrivals. Th ese studies have focused on the tourist arrivals to Turkey countr...

The Role of the Kalman Filter in Time Series Econometrics

E conomic time series display features such as trend, seasonal, and cycle that we do not observe directly from the data. The cycle is of particular interest to economists as it is a measure of the fl uctuations in economic activity. An unobserved components model attempts to capture the features of a time series by assuming that they follow stochastic processes that, when put together, yield th...

Space–time Kalman filter

Real-time Tracking with Kalman Filter

automatically updated during the matching process, This paper describes a real-time tracking system which detects an object entering into the field of view of camera and executes the tracking of the detected object by controlling a servo device so that a target object always lies at the center of an image frame. In order to detect and track a moving object, we basically apply a model matching s...