msample

Msample is a term used in statistics and computing to denote a sample consisting of m observations drawn from a population or distribution. The exact meaning of msample depends on context, but it generally conveys the idea of a collection of m items selected for analysis.

In statistical practice, an msample can be drawn with or without replacement. With replacement, members can appear more than once; without replacement, each observation is unique. The sampling method affects properties such as bias and variance, and may be designed to reflect the population structure or study design.

In computing and data analysis, msample often refers to a function or operation that returns m random samples from a data source or probability distribution. Typical parameters include the source (data array or distribution), m (the number of samples), replacement (whether sampling is with replacement), and an optional seed to ensure reproducibility.

Applications include Monte Carlo simulations, bootstrapping, hypothesis testing, and estimation procedures. In streaming or big-data contexts, msampling algorithms may operate in an online or distributed fashion to produce samples efficiently while limiting memory usage.

See also: sampling, bootstrap, Monte Carlo method, random sampling, resampling.