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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 residuals cannot be expressed analytically or are too time consuming to be evaluate repeatedly, as it is often the case in iterative minimization ...
There are four categories on a 2*2 matrix; horizontal is scale of payoff (or benefits), vertical is ease of implementation. By deciding where an idea falls on the pick chart four proposed project actions are provided; Possible, Implement, Challenge and Kill (thus the name PICK). Low Payoff, easy to do - Possible High Payoff, easy to do - Implement
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Partial least squares (PLS) regression is a statistical method that bears some relation to principal components regression and is a reduced rank regression; [1] instead of finding hyperplanes of maximum variance between the response and independent variables, it finds a linear regression model by projecting the predicted variables and the observable variables to a new space of maximum ...
A3 problem solving is a structured problem-solving and continuous-improvement approach, first employed at Toyota and typically used by lean manufacturing practitioners. [1] It provides a simple and strict procedure that guides problem solving by workers. The approach typically uses a single sheet of ISO A3-size paper, which is the source of its ...
PLS-PM [4] [5] is a component-based estimation approach that differs from the covariance-based structural equation modeling.Unlike covariance-based approaches to structural equation modeling, PLS-PM does not fit a common factor model to the data, it rather fits a composite model.
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