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Bayesian structural time series (BSTS) model is a statistical technique used for feature selection, time series forecasting, nowcasting, inferring causal impact and other applications. The model is designed to work with time series data. The model has also promising application in the field of analytical marketing. In particular, it can be used ...
Dataframe may refer to: A tabular data structure common to many data processing libraries: pandas (software) § DataFrames; The Dataframe API in Apache Spark;
SAP BW Accelerator includes indexes that are vertically inverted reproductions of all the data included in InfoCubes (i.e., fact and dimension tables as well as master data). [2] Note that there is no relational or other database management systems in BW Accelerator. There is only a file system, and indexes are essentially held as flat files.
[4]: 112 Series can be used arithmetically, as in the statement series_3 = series_1 + series_2: this will align data points with corresponding index values in series_1 and series_2, then add them together to produce new values in series_3. [4]: 114 A DataFrame is a 2-dimensional data structure of rows and columns, similar to a spreadsheet, and ...
SAP Business Warehouse (SAP BW) is SAP’s Enterprise Data Warehouse product. [1] It can transform and consolidate business information from virtually any source system. [citation needed] It ran on industry standard RDBMS until version 7.3 at which point it began to transition onto SAP's HANA in-memory DBMS, particularly with the release of version 7.4.
In time series analysis used in statistics and econometrics, autoregressive integrated moving average (ARIMA) and seasonal ARIMA (SARIMA) models are generalizations of the autoregressive moving average (ARMA) model to non-stationary series and periodic variation, respectively.
Main concerns for data differencing are usability and space efficiency (patch size).. If one simply wishes to reconstruct the target given the source and patch, one may simply include the entire target in the patch and "apply" the patch by discarding the source and outputting the target that has been included in the patch; similarly, if the source and target have the same size one may create a ...
Conversely, if the process requires differencing to be made stationary, then it is called difference stationary and possesses one or more unit roots. [2] [3] Those two concepts may sometimes be confused, but while they share many properties, they are different in many aspects. It is possible for a time series to be non-stationary, yet have no ...