Stochastic drift
From Wikipedia, the free encyclopedia
The word stochastic (Gr. στωχος, guess) means random, pertaining to chance. Stochastic models are based on random trials and usually envelope a randomly determined sequence of observations.
[edit] Stochastic drifts
Longitudinal studies of secular events are frequently conceptualized as consisting of a trend component fitted by a polynomial, a cyclical component often fitted by an analysis based on autocorrelations or on a Fourier series, and a random component (stochastic drift) to be removed.
In the course of the time series analysis, identification of cyclical and stochastic drift components is often attempted by alternating autocorrelation analysis and differencing of the trend. Autocorrelation analysis helps to identify the correct phase of the fitted model while the successive differencing transforms the stochastic drift component into white noise.
Stochastic Drift can also occur in population genetics where it is known as Genetic drift. A finite population of randomly-reproducing organisms would experience changes from generation to generation in the frequencies of the different genotypes. This may lead to the fixation of one of the genotypes, and even the emergence of a new species. In sufficiently small populations, drift can also neutralize the effect of deterministic natural selection on the population.
[edit] References
- Krus, D.J., & Ko, H.O. (1983) Algorithm for autocorrelation analysis of secular trends. Educational and Psychological Measurement, 43, 821-828. (Request reprint).
- Krus, D. J., & Jacobsen, J. L. (1983) Through a glass, clearly? A computer program for generalized adaptive filtering. Educational and Psychological Measurement, 43, 149-154
