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\dontrun{} with unwrapped examples or
\donttest{} per CRAN policy.Trehafod and glme.gev11() examples
in \donttest{} (> 5 sec on Debian).glme.gev() output names
changed for consistency:
lme → para.lmeglme → para.glmenllh.pref → nllh.glmecovinv → covinv.lmomma.gev() output names
changed for consistency:
zp.ma → qua.mazp.bma → qua.bmafin.se.ma → fixw.se.maadj.se.ma → ranw.se.manumk_ma and numk_bma →
run.numkpick_xi_ma and pick_xi_bma →
pick_xiremle1 → para.remle1 (in return and
internal use)remle2 → para.remle2 (in return and
internal use)::: accessor):
init.glme() → init.gevmax()new_pf_norm() → pk.norm.stnary() (with
backward-compatible alias)gev.rl.delta_new() → gev.rl.delta()lme.boots.new() → lme.boots()cand.xi.new.paper() → cand.xi()weight.com.new() → weight.com()cov.interp.new() → cov.interp()gev.profxi.mdfy.paper() →
gev.profxi.mdfy()comp.prof.ci.new() → comp.prof.ci()gev1.CD() → mle.gev.CD()gev.remle() → remle.gev()ginit.max() → init.gevmax()pargev.xifix.ma() → pargev.xifix()set.prior() now use
pk.beta.stnary() from glme.gev.Rglme.gev11() output
para.jkss renamed to para.lme for consistency.
Users accessing result$para.jkss should update their code
to use result$para.lme.glme.gev11() and
gado.prop_11() output strup.final renamed to
para.wls. Users accessing result$strup.final
should update their code to use result$para.wls.glme.gev11() no longer
returns strup.sta in its output.glme.gev11() with new parameters:
glme.pre = "wls": Pre-estimation method selection
(“wls” or “gado”)choose = "gof": Model selection criterion (“gof” for
goodness-of-fit, “nllh” for negative log-likelihood)pen.choice = 6: Default penalty hyperparameter choice
changed from NULL to 6quagev.NS() function for calculating quantiles from
non-stationary GEV models
ma.gev() with new estimation options:
CD = TRUE: Coles-Dixon penalized MLE for shape
parameter regularizationremle = TRUE: Restricted MLE with mean/median
constraintsmle.CD, qua.CD,
remle1, remle2, qua.remle1,
qua.remle2quant in output for conveniencebma.se.between and
bma.se.withinmagev.ksensplot(): K sensitivity analysis to select
optimal number of submodelsmagev.qqplot(): 2x2 Q-Q diagnostic plot comparing MLE,
LME, surrogate, and REMLEmagev.rlplot(): Return level plot with 95% confidence
intervalsbangkok dataset: Annual maximum daily rainfall
from Bangkok, Thailandhaenam dataset: Annual maximum daily rainfall
from Haenam, South Koreanumq = 1) in
ma.gev()ma.gev()) for
high quantile estimation.
like, gLd,
med, cvt and variantsbma=TRUE) with
normal/beta priorsqua.ma) with standard
errorsismev, Rsolnp,
zoo.glme.gev()).glme.gev11())
where location (mu) and scale (sigma) parameters vary linearly with
time.
para.glme: Proposed GLME estimatespara.lme: L-moment based estimates for non-stationary
modelnsgev(): Simple interface for L-moment based
non-stationary estimationgado.prop_11(): Comprehensive estimation with multiple
methods"beta" (default),
"norm", "ms" (Martins-Stedinger),
"park", "cannon", "cd"
(Coles-Dixon), and "no" (no penalty).pen.choice or
direct parameters (p, c1, c2 for
beta; mu, std for normal penalty).streamflow,
PhliuAgromet, and Trehafod.These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.