Lastparametrarna

Lastparametrarna is a term used in Swedish-language technical literature to refer to the final set of parameters produced by an iterative estimation or optimization process. The word combines last, meaning final, with parametrarna, the definite plural form of parameters. The concept is used across disciplines such as data science, machine learning, statistics, and control theory to denote the model configuration reached when a stopping criterion is met.

In practice, lastparametrarna capture the state of a model after training or after a sequence of updates. They are reported to characterize the resulting model, enable reproducibility, and serve as a basis for further analysis, such as sensitivity tests or comparative studies. The exact values depend on initialization, optimization algorithm, learning rate schedule, regularization, and stopping rules, so the same problem can yield different lastparametrarna under different settings.

Examples appear across fields: in machine learning, the lastparametrarna may be the final weight vector after training a neural network or linear model; in time-series forecasting, they may represent the parameter estimates after iterative refinement; in adaptive control, they reflect stabilized estimates used to compute control actions. Reporting lastparametrarna is often accompanied by metadata about the method, data subset, and convergence criteria to support interpretation and reproducibility.

Limitations include susceptibility to local optima, initialization bias, and the influence of hyperparameters. Therefore, researchers commonly accompany lastparametrarna with diagnostics, validation results, and analyses of parameter stability rather than relying on them alone. Related concepts include parameter estimation, convergence criteria, and model selection.