The first observation window is preceded by a first portion of the first time series. A neural network is trained using the first portion of the first time series and the first observation window, and weights are extracted from the middle layers of the neural network. A first feature vector ...
Relational Data Model In applications that use a relational data model, the schema is always defined first. In the case of time-series data, there is always a timestamp column. In addition, each metric has a dedicated column and a data type. There are advantages to this. For e.g. the...
Mining Time Series data has a tremendous growth of interest in today's world. Clustering time series is a trouble that has applications in an extensive assortment of fields and has recently attracted a large amount of researchers. Time series data are frequently large and may contain outliers. ...
Historically, traditional methods such as Autoregressive Integrated Moving Average (ARIMA) have played an important role for researchers studying time series data. Recently, as advances in computer science and machine learning have gained widespread attention, researchers of time series analysis have brought...
In particular, the debate regarding trend versus difference stationarity in macroeconomic trending data is considered. The interest in the present paper is ... D Griffiths - 《Applied Economics》 被引量: 5发表: 2004年 加载更多 研究点推荐 time series data ...
COMPARISON OF ENVIRONMENTAL QUALITY-INDUCED DEMAND SHIFTS USING TIME-SERIES AND CROSS-SECTION DATA Almost all applications of the Travel-Cost-Method demand function which include site quality variable(s) are multisite models. The results of this study se... J Loomis,JC Cooper - 《Western Journal...
This research compares partial equilibrium and statistical time-series approaches to hedging. The finance literature stresses the former approach, while the applied economics literature has focused on the latter. We compare the out-of-sample hedging effectiveness of the two approaches when hedging commodi...
However, those studies were performed for univariate data only. The present work uses six variables in a time series and compares the multivariate and the univariate models. In [72], the model that presents the lowest RMSE is the ARIMA. However, that is just for a small dataset and ...
and databases can be included and benchmarked. To this end we hope to help prospective database administrators find the best database for their needs and their workloads. Further, if you are the developer of a time series database and want to include your database in the TSBS, feel free ...
and databases can be included and benchmarked. To this end we hope to help prospective database administrators find the best database for their needs and their workloads. Further, if you are the developer of a time series database and want to include your database in the TSBS, feel free ...