Modernizing Probable Maximum Precipitation Estimation (2024) / Chapter Skim
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Appendix E: R Code used in Report Figures 3-5 and 5-3
Pages 193-196

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From page 193...
... ## R version: 4.3.2 library(evd) # Version 2.3-6.1 ## Location and scale parameter estimates from GEV fit to GHCN daily ## precipitation data for for Berkeley, California, but qualitative ## results are similar for parameters from GEV fits for other US locations.
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From page 194...
... { ## Calculates sample size needed to limit the standard error of the estimated ## return value (or upper bound) to `se_proportion` of the estimate, using ## the expected information matrix for the GEV distribution and the delta method ## to approximate the variance of the estimate as a function of the estimated ## parameters.
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From page 195...
... % cov_mtx %* % grad_vec ## Invert to determine sample size.
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From page 196...
... location <- 4.5 scale <- 1.5 shape <- 0 calc_sample_size(location, scale, shape, return_period = 10000, se_proportion = 0.125) ## Sample size for estimating upper bound.
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Key Terms

  • upper bound
  • delta method
  • values based
  • calculate variance
  • gev fit

  • providing param
  • determine sample
  • scale parameter
  • value based
  • estimating upper

  • wrapper providing
  • precipitation data
  • parameter estimates
  • ghcn daily
  • gev fits

  • return value
  • expected information
  • observation values
  • param vec
  • sample size

  • prepublication copy
  • trapezoidal rule
  • estimate integral
  • uc berkeley
  • evaluate density

  • christopher paciorek


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