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For estimation of a variable of interest using Kalman filter by incorporating results from previous assessments, i.e. through development weighted estimates where weights are assigned inversely proportional to the variance of existing and new estimates. For reference see Ehlers et al. (2017) <doi:10.20944/preprints201710.0098.v1>.

Type Size Name Uploaded Downloads Labels
conda 66.7 kB | linux-64/r-datassim-1.0-r43h884c59f_0.tar.bz2  1 year and 1 month ago 23 main
conda 67.4 kB | linux-64/r-datassim-1.0-r42h884c59f_0.tar.bz2  2 years and 7 months ago 55 main
conda 69.9 kB | win-64/r-datassim-1.0-r36h796a38f_0.tar.bz2  4 years and 11 months ago 60 main
conda 66.7 kB | osx-64/r-datassim-1.0-r36h466af19_0.tar.bz2  4 years and 11 months ago 19 main
conda 65.2 kB | linux-64/r-datassim-1.0-r36h29659fb_0.tar.bz2  4 years and 11 months ago 55 main

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