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Notes: A Continuous-Time Markov Chain for Early Selections

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Abstract:

A discrete stepwise Markov chain for predicting relative performance of early selections at time of harvest is transformed into a continuous-time Markov chain by a simple transformation to a canonical form. Asymptotic predictions for t → ∞ are made possible. Prediction errors are derived from an autoregressive scheme and assumptions of multinominal one-step ahead errors. For. Sci. 39(4):845-850.

Keywords: Eigenvalues; asymptotic predictions; errors; predictions; size distribution; steady state

Document Type: Miscellaneous

Affiliations: Canadian Forest Service, Chalk River, Ontario, Canada K0J1J0

Publication date: November 1, 1993

More about this publication?
  • Forest Science is a peer-reviewed journal publishing fundamental and applied research that explores all aspects of natural and social sciences as they apply to the function and management of the forested ecosystems of the world. Topics include silviculture, forest management, biometrics, economics, entomology & pathology, fire & fuels management, forest ecology, genetics & tree improvement, geospatial technologies, harvesting & utilization, landscape ecology, operations research, forest policy, physiology, recreation, social sciences, soils & hydrology, and wildlife management.
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