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  2. Non-linear least squares - Wikipedia

    en.wikipedia.org/wiki/Non-linear_least_squares

    Consider a set of data points, (,), (,), …, (,), and a curve (model function) ^ = (,), that in addition to the variable also depends on parameters, = (,, …,), with . It is desired to find the vector of parameters such that the curve fits best the given data in the least squares sense, that is, the sum of squares = = is minimized, where the residuals (in-sample prediction errors) r i are ...

  3. Error correction model - Wikipedia

    en.wikipedia.org/wiki/Error_correction_model

    The term error-correction relates to the fact that last-period's deviation from a long-run equilibrium, the error, influences its short-run dynamics. Thus ECMs directly estimate the speed at which a dependent variable returns to equilibrium after a change in other variables.

  4. Omitted-variable bias - Wikipedia

    en.wikipedia.org/wiki/Omitted-variable_bias

    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;

  5. Propagation of uncertainty - Wikipedia

    en.wikipedia.org/wiki/Propagation_of_uncertainty

    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 ...

  6. Category:Errors reported by Module String - Wikipedia

    en.wikipedia.org/wiki/Category:Errors_reported...

    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.

  7. Errors-in-variables model - Wikipedia

    en.wikipedia.org/wiki/Errors-in-variables_model

    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.

  8. Error detection and correction - Wikipedia

    en.wikipedia.org/wiki/Error_detection_and_correction

    Error-correcting codes are used in lower-layer communication such as cellular network, high-speed fiber-optic communication and Wi-Fi, [11] [12] as well as for reliable storage in media such as flash memory, hard disk and RAM. [13] Error-correcting codes are usually distinguished between convolutional codes and block codes:

  9. Errors and residuals - Wikipedia

    en.wikipedia.org/wiki/Errors_and_residuals

    Since this is a biased estimate of the variance of the unobserved errors, the bias is removed by dividing the sum of the squared residuals by df = n − p − 1, instead of n, where df is the number of degrees of freedom (n minus the number of parameters (excluding the intercept) p being estimated - 1). This forms an unbiased estimate of the ...