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  2. Errors-in-variables model - Wikipedia

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

    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.

  3. Seemingly unrelated regressions - Wikipedia

    en.wikipedia.org/wiki/Seemingly_unrelated...

    Suppose there are m regression equations = +, =, …,. Here i represents the equation number, r = 1, …, R is the individual observation, and we are taking the transpose of the column vector.

  4. Technique for human error-rate prediction - Wikipedia

    en.wikipedia.org/wiki/Technique_for_human_error...

    THERP is a first-generation methodology, which means that its procedures follow the way conventional reliability analysis models a machine. [3] The technique was developed in the Sandia Laboratories for the US Nuclear Regulatory Commission. [4]

  5. Estimand - Wikipedia

    en.wikipedia.org/wiki/Estimand

    An estimand is a quantity that is to be estimated in a statistical analysis. [1] The term is used to distinguish the target of inference from the method used to obtain an approximation of this target (i.e., the estimator) and the specific value obtained from a given method and dataset (i.e., the estimate). [2]

  6. Estimation theory - Wikipedia

    en.wikipedia.org/wiki/Estimation_theory

    Estimation theory is a branch of statistics that deals with estimating the values of parameters based on measured empirical data that has a random component. The parameters describe an underlying physical setting in such a way that their value affects the distribution of the measured data.

  7. Pseudolikelihood - Wikipedia

    en.wikipedia.org/wiki/Pseudolikelihood

    In statistical theory, a pseudolikelihood is an approximation to the joint probability distribution of a collection of random variables.The practical use of this is that it can provide an approximation to the likelihood function of a set of observed data which may either provide a computationally simpler problem for estimation, or may provide a way of obtaining explicit estimates of model ...

  8. A priori estimate - Wikipedia

    en.wikipedia.org/wiki/A_priori_estimate

    In the theory of partial differential equations, an a priori estimate (also called an apriori estimate or a priori bound) is an estimate for the size of a solution or its derivatives of a partial differential equation.

  9. Group-contribution method - Wikipedia

    en.wikipedia.org/wiki/Group-contribution_method

    The simplest form of a group-contribution method is the determination of a component property by summing up the group contributions : [] = +.This simple form assumes that the property (normal boiling point in the example) is strictly linearly dependent on the number of groups, and additionally no interaction between groups and molecules are assumed.