stapgroottes

Stapgroottes (step sizes) is the size of the discrete increments used when converting a continuous model to a discrete representation, and more generally the size of each step in an iterative calculation. The term is used in Dutch-language literature to discuss how finely a process is sampled or advanced in time or space, and it is often denoted by h or Δt in equations.

In solving differential equations numerically, stapgroottes determine the time step or spatial grid spacing. A smaller step increases accuracy and stability but raises computational cost. Many methods have stability constraints (for example CFL conditions for explicit schemes) that impose an upper bound on the step size for a given problem.

In data analysis and signal processing, stapgroottes appear as bin widths in histograms, sampling intervals in time series, or quantization steps in digital representations. These choices influence resolution, noise behavior, and interpretation of results.

Practitioners often assess convergence by reducing the stapgrottes and comparing results, or use adaptive step-size algorithms that adjust the step based on estimated error. Nonuniform step sizes can accommodate varying scales within a problem.

See also: discretization, numerical methods, time stepping, grid size, bin width, quantization, adaptive step size.