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The Kalman filter is a multivariate generalization of the composite estimator which recursively combines a current direct estimate with a past estimate that is updated for expected change over time with a prediction model. The Kalman filter can estimate proportions of different cover types for sub-…
Author(s): Raymond L. Czaplewski
Keywords: Kalman filter, forest cover, statistical monitoring, estimate
Source: Biometric Bulletin. 8(4): 6016.
Year: 1991
The Kalman filter is a generalization of the composite estimator. The univariate composite estimate combines 2 prior estimates of population parameter with a weighted average where the scalar weight is inversely proportional to the variances. The composite estimator is a minimum variance estimator…
Author(s): Raymond L. Czaplewski
Keywords: Kalman filter, forest cover, statistical monitoring, estimate
Source: In: 4th Symposium on Biometrical Problems in Agriculture, Forestry and Animal Investigations; 19-21 August, Jokioinen, Finland. Washington, DC: The International Biometric Society. 7 p.
Year: 1991
Contemporary efforts to conserve populations and species often employ population viability analysis (PVA), a specific application of population modeling that estimates the effects of environmental and demographic processes on population growth rates. These models can also be used to estimate…
Author(s): Carolyn Hull Sieg, Rudy M. King, Fred Van Dyke
Keywords: population viability analysis (PVA), western prairie fringed orchid, estimate, population
Source: In: Van Dyke, Fred, ed. A Workbook In Conservation: Solving Practical Problems in Conservation. New York, NY: McGraw-Hill. p. 91-99.
Year: 2003
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