ks: Kernel Smoothing
Kernel smoothers for univariate and multivariate data, with comprehensive visualisation and bandwidth selection capabilities, including for densities, density derivatives, cumulative distributions, clustering, classification, density ridges, significant modal regions, and two-sample hypothesis tests. Chacon & Duong (2018) <doi:10.1201/9780429485572>.
Version:
1.15.1
Depends:
R (≥ 2.10.0)
Published:
2025年05月04日
Maintainer:
Tarn Duong <tarn.duong at gmail.com>
NeedsCompilation:
yes
Documentation:
Downloads:
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agfh,
bayesammi,
BEKKs,
birdring,
blocs,
bspcov,
cdcsis,
changepoints,
curvHDR,
diggit,
DMTL,
ecospat,
eks,
enmSdmX,
fdaSP,
feature,
fishboot,
FitDynMix,
fitPS,
flowStats,
funspace,
GMC,
goffda,
GPareto,
habtools,
hdrcde,
highriskzone,
HybridMicrobiomes,
hypervolume,
lg,
logcondens,
lsbs,
metaGE,
motmot,
movieROC,
multimode,
Nebulosa,
NMADTA,
npphen,
NTSS,
oddstream,
OVL.CI,
powerPLS,
qch,
Racmacs,
rainbow,
raptr,
reconsi,
refreg,
RRgeo,
rugarch,
semiArtificial,
shinyWGD,
simIReff,
simlandr,
simukde,
smoothROCtime,
sNPLS,
SPARTAAS,
starvars,
stppSim,
stray,
Surrogate,
ThresholdROC,
tseriesEntropy,
tstests,
USE,
VIRF,
weird,
winputall,
YEAB
Reverse suggests:
broom,
causalBatch,
clustNet,
condvis2,
fdapace,
ggsc,
httk,
InteractiveComplexHeatmap,
kedd,
kernelboot,
mable,
np,
nullranges,
polykde,
scorematchingad,
sensitivity,
spatialEco,
SVP,
transport
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