Category: Learning modules
This article, discusses and interprets the rest of the results from Malmquist DEA. Furthermore, the analysis of Malmquist index summaries for both output and input frontiers are interpreted.
DEA module, malmquist dea, result interpretationDifferences between Multi-stage and Cost- data envelopment analysis (DEA) was also discussed. However, the article will only interpret the results from cost efficiency analysis from the constant returns to scale (CRS) frontier.
dea cost efficiency, DEA moduleThe Comprehensive Meta-analysis (CMA) software is a user-friendly and diverse software. It is capable of handling and executing multiple tests involved in performing Meta-analysis.
CMA, CMA introductionIn the previous article, discussed and interpreted the findings of cost efficiency using constant returns to scale (CRS) Cost Data Envelopment Analysis (DEA).
dea cost efficiency, DEA moduleThe cost efficiency analysis or cost data envelopment analysis or cost DEA is evaluated when information on prices and costs are available from the source of the data collected for input and output variables (Cooper, Seiford, & Zhu, 2011).
dea cost efficiency, DEA moduleOutliers are those data points which are distant from the other observations in the data set. They can be either because of the variability in the data set or due to measurement errors.
detection in supervised learning, Supervised learning, trend analysisThe previous article based on the Dickey-Fuller test established that GDP time series data is non-stationary.
assumption tests in STATA, empirical analysis with econometrics, STATA for data analysis, stationarity test, time series analysisIn statistics, Generalized Least Squares (GLS) is one of the most popular methods for estimating unknown coefficients of a linear regression model when the independent variable is correlating with the residuals.
detection in supervised learning, Supervised learning