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An undefined variable in the source code of a computer program is a variable that is accessed in the code but has not been declared by that code. [1] In some programming languages, an implicit declaration is provided the first time such a variable is encountered at compile time. In other languages such a usage is considered to be sufficiently ...
This category is a catch-all for errors reported by Module:String. Such errors generally occur due to incorrect parameters, such as indices that are out of range for the strings being examined. Users of Module:String may also specify an alternative cat to use via the error_category= parameter.
203 Non-Authoritative Information (since HTTP/1.1) The server is a transforming proxy (e.g. a Web accelerator) that received a 200 OK from its origin, but is returning a modified version of the origin's response. [1]: §15.3.4 [1]: §7.7 204 No Content The server successfully processed the request, and is not returning any content.
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In an economic model, an exogenous variable is one whose measure is determined outside the model and is imposed on the model, and an exogenous change is a change in an exogenous variable. [1]: p. 8 [2]: p. 202 [3]: p. 8 In contrast, an endogenous variable is a variable whose measure is determined by the model. An endogenous change is a change ...
β is a p × 1 column vector of unobservable parameters (the response coefficients of the dependent variable to each of the p independent variables in x i) to be estimated; z i is a scalar and is the value of another independent variable that is observed at time i or for the i th study participant;
Linear errors-in-variables models were studied first, probably because linear models were so widely used and they are easier than non-linear ones. Unlike standard least squares regression (OLS), extending errors in variables regression (EiV) from the simple to the multivariable case is not straightforward, unless one treats all variables in the same way i.e. assume equal reliability.
Any non-linear differentiable function, (,), of two variables, and , can be expanded as + +. If we take the variance on both sides and use the formula [11] for the variance of a linear combination of variables (+) = + + (,), then we obtain | | + | | +, where is the standard deviation of the function , is the standard deviation of , is the standard deviation of and = is the ...