Leading Indicators of Regional Cotton Acreage Response: Structural and Time Series Modeling Results

Learning leading indicators for time-series predictions

While the importance of Granger-causal (G-causal) relationships for learning vector autoregressive models (VARs) is widely acknowledged, the state-of-theart VAR methods do not address the problem of discovering the underlying Gcausality structure in a principled manner. VAR models can be restricted if such restrictions are supported by a strong domain theory (e.g. economics), but without such s...

Modeling and prediction of time-series of monthly copper prices

One of the main tasks to analyze and design a mining system is predicting the behavior exhibited by prices in the future. In this paper, the applications of different prediction methods are evaluated in econometrics and financial management fields, such as ARIMA, TGARCH, and stochastic differential equations, for the time-series of monthly copper prices. Moreover, the performance of these metho...

Time Series Modeling of Coronavirus (COVID-19) Spread in Iran

Various types of Coronaviruses are enveloped RNA viruses from the Corona-viridae family and part of the Coronavirinae subfamily. This family of viruses affects neurological, gastrointestinal, hepatic, and respiratory systems. Recently, a new memb-er of this family, named Covid-19, is moving around the world. The expansion of Covid-19 carries many risks, and its control requires strict planning ...

Learning Predictive Leading Indicators for Forecasting Time Series Systems with Unknown Clusters of Forecast Tasks

We present a new method for forecasting systems of multiple interrelated time series. The method learns the forecast models together with discovering leading indicators from within the system that serve as good predictors improving the forecast accuracy and a cluster structure of the predictive tasks around these. The method is based on the classical linear vector autoregressive model (VAR) and...

State-Space Time Series Modeling of Structural Breaks