Parametrarna

Parametrarna is the Swedish term used to refer collectively to the parameters that define a model, system, or process. The word is formed from parameter with the definite plural suffix -arna and is typically used in Swedish-language technical writing to denote a specific, identifiable set of quantities.

In mathematics and statistics, Parametrarna refer to unknown quantities that must be specified or inferred from data. They determine the form of a model and its predictions, for example the coefficients in a linear regression or the shape parameters of a probability distribution.

In data science and machine learning, Parametrarna of a model typically include the weights and biases of a neural network, or the coefficients in a regression model. Hyperparameters, such as learning rate or regularization strength, are usually considered separately from Parametrarna.

In physics and engineering, Parametrarna specify system properties (material constants, damping coefficients) and external conditions (initial states, forcing functions) that influence the behavior of a model or simulation. Calibrating Parametrarna against observed data is a common task in model validation.

Parameter estimation methods commonly used include maximum likelihood, least squares, and Bayesian inference, depending on the context and assumptions. In practice, documenting Parametrarna clearly is essential for reproducibility and for interpreting model outputs.

See also: parameter, parametric model, parameter estimation.