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Mixed-data sampling (MIDAS) is an econometric regression developed by Eric Ghysels with several co-authors. There is now a substantial literature on MIDAS regressions and their applications, including Ghysels, Santa-Clara and Valkanov (2006), [ 1 ] Ghysels, Sinko and Valkanov, [ 2 ] Andreou, Ghysels and Kourtellos (2010) [ 3 ] and Andreou ...
In finance, MIDAS (an acronym for Market Interpretation/Data Analysis System) is an approach to technical analysis initiated in 1995 by the physicist and technical analyst Paul Levine, PhD, [1] and subsequently developed by Andrew Coles, PhD, and David Hawkins in a series of articles [2] and the book MIDAS Technical Analysis: A VWAP Approach to Trading and Investing in Today's Markets. [3]
This is a list of statistical procedures which can be used for the analysis of categorical data, also known as data on the nominal scale and as categorical variables.
In statistical quality control, the ¯ and s chart is a type of control chart used to monitor variables data when samples are collected at regular intervals from a business or industrial process. [1] This is connected to traditional statistical quality control (SQC) and statistical process control (SPC).
MIDAS (Maximum Integration Data Acquisition System) has been developed as a general purpose data acquisition system for small and medium scale experiments originally by Stefan Ritt in 1993, followed by Pierre-André Amaudruz in 1996. It is written in C and published under the GPL.
Data collection and validation consist of four steps when it involves taking a census and seven steps when it involves sampling. [3] A formal data collection process is necessary, as it ensures that the data gathered are both defined and accurate. This way, subsequent decisions based on arguments embodied in the findings are made using valid ...
In statistics and econometrics, cross-sectional data is a type of data collected by observing many subjects (such as individuals, firms, countries, or regions) at a single point or period of time. Analysis of cross-sectional data usually consists of comparing the differences among selected subjects, typically with no regard to differences in time.
Example: the visual shows music listened to by a user over time; Treemap: Treemap: size; color; Is a method for displaying hierarchical data using nested figures, usually rectangles. For example, disk space by location / file type; Gantt chart: Gantt chart: color; time (flow) Type of bar chart that illustrates a project schedule