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Effective field theories in physics can include quantum field theories in which the fields are treated as fundamental, and effective theories describing phenomena in solid-state physics. For instance, the BCS theory of superconduction treats vibrations of the solid-state lattice as a " field " (i.e. without claiming that there is really a field ...
Effective field theories typically work best when there is a large separation between length scale of interest and the length scale of the underlying dynamics. Effective field theories have found use in particle physics , statistical mechanics , condensed matter physics , general relativity , and hydrodynamics .
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 ...
Simply stated, effective means achieving an effect, and efficient means getting a task or job done it with little waste. To illustrate: suppose, you build 10 houses, very fast and cheap (efficient), but no one buy them. In contrary to building 5 houses same budget and time as 10 houses but you get all 5 sold and the buyers are happy (effective).
The time series included yearly, quarterly, monthly, daily, and other time series. In order to ensure that enough data was available to develop an accurate forecasting model, minimum thresholds were set for the number of observations: 14 for yearly series, 16 for quarterly series, 48 for monthly series, and 60 for other series.
Interrupted time series design is the design of experiments based on the interrupted time series approach. The method is used in various areas of research, such as: political science : impact of changes in laws on the behavior of people; [ 2 ] (e.g., Effectiveness of sex offender registration policies in the United States )
Ideally, unevenly spaced time series are analyzed in their unaltered form. However, most of the basic theory for time series analysis was developed at a time when limitations in computing resources favored an analysis of equally spaced data, since in this case efficient linear algebra routines can be used and many problems have an explicit ...
In order to still use the Box–Jenkins approach, one could difference the series and then estimate models such as ARIMA, given that many commonly used time series (e.g. in economics) appear to be stationary in first differences. Forecasts from such a model will still reflect cycles and seasonality that are present in the data.