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A Product fit analysis (PFA) is a form of requirements analysis of the gap between an IT product's functionality and required functions. It is a document which consists of all the business requirements which are mapped to the product or application .
In management literature, gap analysis involves the comparison of actual performance with potential or desired performance. [1] If an organization does not make the best use of current resources, or forgoes investment in productive physical capital or technology, it may produce or perform below an idealized potential.
XLfit is a Microsoft Excel add-in that can perform regression analysis, curve fitting, and statistical analysis. It is approved by the UK National Physical Laboratory and the US National Institute of Standards and Technology [1] XLfit can generate 2D and 3D graphs and analyze data sets. XLfit can also analyse the statistical data.
Discovery, analysis, and specification move the understanding from a current as-is state to a future to-be state. Requirements specification can cover the full breadth and depth of the future state to be realized, or it could target specific gaps to fill, such as priority software system bugs to fix and enhancements to make.
A gap is defined as an unfilled space or interval. On a technical analysis chart, a gap represents an area where no trading takes place. On the Japanese candlestick chart, a window is interpreted as a gap. Gaps are spaces on a chart that emerge when the price of the financial instrument significantly changes with little or no trading in between.
Engineering fits are generally used as part of geometric dimensioning and tolerancing when a part or assembly is designed. In engineering terms, the "fit" is the clearance between two mating parts, and the size of this clearance determines whether the parts can, at one end of the spectrum, move or rotate independently from each other or, at the other end, are temporarily or permanently joined.
It is one approach to handling the "errors in variables" problem, and is also sometimes used even when the covariates are assumed to be error-free. Linear Template Fit (LTF) [7] combines a linear regression with (generalized) least squares in order to determine the best estimator. The Linear Template Fit addresses the frequent issue, when the ...
Curve fitting [1] [2] is the process of constructing a curve, or mathematical function, that has the best fit to a series of data points, [3] possibly subject to constraints. [ 4 ] [ 5 ] Curve fitting can involve either interpolation , [ 6 ] [ 7 ] where an exact fit to the data is required, or smoothing , [ 8 ] [ 9 ] in which a "smooth ...